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Book Synopsis Python Programming for Beginners - Book 1 by : Martin Evans
Download or read book Python Programming for Beginners - Book 1 written by Martin Evans and published by Martin Evans. This book was released on 2020-12-27 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Beginner's Guide Offers You the Easiest Way to Learn Everything About Python! Dear reader, Are you interested in Computer Science? Would you like to develop strong skills in Python programming? If you are reading this, it means that you already made a first step towards achieving that goal. It also means that you have a desire to learn, and this guide has the means to give you all the knowledge you are hungry for. Other guides you can find on the market focus too much on a pure theory and have a theoretical approach that is hard to understand. This guide aims to deliver the needed knowledge through practical exercises and unique coding techniques. With this guide in your hands, you will quickly learn everything you need to know about Python and successfully acquire the skills necessary for Python programming. Here's what this guide can offer you: - Basics of programming with Python - Guide to essential programming tools and techniques - How to get everything up and running - Practical techniques and exercises - Guide for making your first program It doesn't even matter if you never wrote a single line of code in your life because this guide is made specifically for beginners. Everything you need to learn is presented through step-by-step directions and easy to digest topics. Here is what else you will learn: - How to Create Your First Program - How to Work with Files on Python - How to deal with Classes and Objects - How to Work with Exception Handling - How to use Operators in Your Code If you want an easy way to acquire Python programming skills and knowledge about data science, all you have to do is follow the easy step-by-step instructions and exercises found in this guide. So what are you waiting for? Scroll up, click on "Buy Now with 1-Click", and Get Your Copy Now!
Book Synopsis Python Programming for Beginners – 5 in 1 Crash Course by : Martin Evans
Download or read book Python Programming for Beginners – 5 in 1 Crash Course written by Martin Evans and published by Martin Evans. This book was released on 2020-12-27 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you ready to learn the most powerful and popular programming language in the world? Code is the language of the future. And the time to learn the ins and outs of coding is now, unless of course you want to be left behind from the biggest revolution that mankind will witness. If for whatever reason, you have been looking to improve your programming skills, Python programming language could be the best option you can get right now. It makes everything so easy! From the rich and well-designed standard library and built-ins to the availability of modules and numerous third-party open-source libraries, very few programming languages can beat it. Deemed as a high-level programming language, it is not surprising that many people find Phyton quite intimidating. Thus, they shy away from learning about it. Starting programming may seem to be a struggle but thanks to this book you will be able to go from a complete beginner in the world of Python and turn yourself into an expert. You will Learn: · The basics of data types, variables, and structures · Working with Python iterators, generators, and descriptors · How to make unique and useful programs · Basic hacking with the help of Python code · Applications and methods of data analysis · And much more! By learning this essential programming language, you will open tons of doors for both your personal and professional life. With Python, opportunities and possibilities are simply endless… Scroll up and click “BUY NOW with 1-Click” to Start Programming Today!
Book Synopsis A beginner's guide to Python by : Abhijit Tripathy
Download or read book A beginner's guide to Python written by Abhijit Tripathy and published by Notion Press. This book was released on 2021-06-24 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python is one of the most prominent programming languages with the rapid growth of applications in different domains like Machine Learning, Web Development, Automation etc. The syntax for python is quite easy from a programmer perspective but there is a ton of things to learn from this syntax. This book provides a clear and concise text for beginners to get started with the python programming language in a simple and systematic way. Read this book to learn some basic concepts of python in an easy manner and apply them to solve 150+ programming problems included in the book. As soon as you complete the book and learned so much about programming in python, there is a hunger to learn more. The next step is jumping into "Data Structures and Algorithms" and cover topics like different sorting, searching, graph, tree, heaps based algorithms by using different new data structures like a stack, queue, binary tree, linked list, array etc. The syntax changes with each language but the concept of the algorithm remains the same in almost every language.
Book Synopsis Python Programming for Beginners - Book 2 by : Martin Evans
Download or read book Python Programming for Beginners - Book 2 written by Martin Evans and published by Martin Evans. This book was released on 2020-12-27 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you ready to learn the most powerful and popular programming language in the world? Code is the language of the future. And the time to learn the ins and outs of coding is now, unless of course you want to be left behind from the biggest revolution that mankind will witness. If for whatever reason, you have been looking to improve your programming skills, Python programming language could be the best option you can get right now. It makes everything so easy! From the rich and well-designed standard library and built-ins to the availability of modules and numerous third-party open source libraries, very few programming languages can beat it. Deemed as a high-level programming language, it is not surprising that many people find Phyton quite intimidating. Thus, they shy away from learning about it. Starting programming may seem to be a struggle but thank to this book you will be able to go from a complete beginner in the world of Python and turn yourself into an expert. You will Learn: - Basics of programming with Python - Python as an Object-Oriented Program - General Methods and Objects - What are Descriptors - Functions Inside of Python - Iterators and Generators - And much more! By learning this essential programming language, you will open tons of doors for both your personal and professional life. With Python, opportunities and possibilities are simply endless… Scroll up and click "BUY NOW with 1-Click" to Start Programming Today!
Book Synopsis A Beginner's Guide To Python Programming by : Abhijit Tripathy
Download or read book A Beginner's Guide To Python Programming written by Abhijit Tripathy and published by Edualgo Academy. This book was released on 2021-01-04 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a clear and concise text for beginners to get started with the python programming language in a simple and systematic way. Read this book to learn some basic concepts of python in an easy manner and apply them to solve 150+ programming problems included in the book. The most important thing about python is that it's open-source. Open-source licensing encourages innovation through collaboration. Without it, many of the technologies we take for granted today would never have developed or would be locked away behind patent law. The open-source movement is the reason that technology has developed at such a breakneck pace for the past few decades. Every year/ session a lot of new features are added to the python programming language that makes it more modern and easier to achieve complex tasks. As soon as you complete the book and learned so much about programming in python, there is a hunger to learn more. The next step is jumping into "Data Structures and Algorithms" and cover topics like different sorting, searching, graph, tree, heaps based algorithms by using different new data structures like a stack, queue, binary tree, linked list, array etc. The syntax changes with each language but the concept of the algorithm remains the same in almost every language.
Book Synopsis Python Programming for Beginners - Book 3 by : Richard Hawkins
Download or read book Python Programming for Beginners - Book 3 written by Richard Hawkins and published by Richard Hawkins. This book was released on 2020-12-27 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Beginner's Guide Offers You the Easiest Way to Learn Everything About Python! Dear reader, Are you interested in Computer Science? Would you like to develop strong skills in Python programming? If you are reading this, it means that you already made a first step towards achieving that goal. It also means that you have a desire to learn, and this guide has the means to give you all the knowledge you are hungry for. Other guides you can find on the market focus too much on a pure theory and have a theoretical approach that is hard to understand. This guide aims to deliver the needed knowledge through practical exercises and unique coding techniques. With this guide in your hands, you will quickly learn everything you need to know about Python and successfully acquire the skills necessary for Python programming. Here's what this guide can offer you: - Basics of programming with Python - Guide to essential programming tools and techniques - How to get everything up and running - Practical techniques and exercises - Guide for making your first program It doesn't even matter if you never wrote a single line of code in your life because this guide is made specifically for beginners. Everything you need to learn is presented through step-by-step directions and easy to digest topics. Here is what else you will learn: - The basics of data types, variables, and structures - Working with Python iterators, generators, and descriptors - How to make unique and useful programs - Basic hacking with the help of Python code - Applications and methods of data analysis - Regular Expressions in Python - How to automate boring stuff quickly If you want an easy way to acquire Python programming skills and knowledge about data science, all you have to do is to follow the easy step-by-step instructions and exercises found in this guide. So what are you waiting for? Scroll up, click on "Buy Now with 1-Click", and Get Your Copy Now!
Book Synopsis Python Programming Guide for GCSE Computer Science (includes Python Files) by : CGP Books
Download or read book Python Programming Guide for GCSE Computer Science (includes Python Files) written by CGP Books and published by CGP Ltd. This book was released on 2022-04-13 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: This brilliant CGP book is the perfect no-nonsense guide for anyone who wants to learn Python! It's packed with clear, friendly notes on all the essential programming skills - ideal for Python beginners, GCSE Computer Science students, and as an introduction to Python at A-Level. There are also stacks of useful practice questions, fully-explained examples and coding challenges to help you become a Python coding pro in no time, with full answers included at the back of the book - fantastic! We've even added over 250 downloadable files covering different areas of Python - they're just the ticket for anyone looking for practical, on-screen practice.
Download or read book Python Programming written by R.H Rizvi and published by R.H Rizvi. This book was released on 2024-08-04 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the full potential of Python with Python Programming A Comprehensive 3-in-1 Guide for Beginners, Intermediates, and Experts by R.H. Rizvi. This all-in-one book is your ultimate resource for mastering Python from scratch. Whether you're just starting out or looking to refine your skills, this guide covers everything from basic syntax and data types to advanced techniques like decorators, context managers, and machine learning. Dive into practical applications with hands-on projects, including web development with Flask and data analysis with libraries like NumPy and Pandas. Perfect for anyone eager to advance their Python knowledge and tackle real-world programming challenges. Get your copy today and embark on a journey to becoming a Python expert!
Book Synopsis Learning Scientific Programming with Python by : Christian Hill
Download or read book Learning Scientific Programming with Python written by Christian Hill and published by Cambridge University Press. This book was released on 2020-11-12 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to master basic programming tasks from scratch with real-life, scientifically relevant examples and solutions drawn from both science and engineering. Students and researchers at all levels are increasingly turning to the powerful Python programming language as an alternative to commercial packages and this fast-paced introduction moves from the basics to advanced concepts in one complete volume, enabling readers to gain proficiency quickly. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving on to the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualization, this textbook also discusses the use of Jupyter Notebooks to build rich-media, shareable documents for scientific analysis. The second edition features a new chapter on data analysis with the pandas library and comprehensive updates, and new exercises and examples. A final chapter introduces more advanced topics such as floating-point precision and algorithm stability, and extensive online resources support further study. This textbook represents a targeted package for students requiring a solid foundation in Python programming.
Book Synopsis C, C++, Java, Python, PHP, JavaScript and Linux For Beginners by : Manjunath.R
Download or read book C, C++, Java, Python, PHP, JavaScript and Linux For Beginners written by Manjunath.R and published by Manjunath.R. This book was released on 2020-04-13 with total page 2272 pages. Available in PDF, EPUB and Kindle. Book excerpt: "An Introduction to Programming Languages and Operating Systems for Novice Coders" An ideal addition to your personal elibrary. With the aid of this indispensable reference book, you may quickly gain a grasp of Python, Java, JavaScript, C, C++, CSS, Data Science, HTML, LINUX and PHP. It can be challenging to understand the programming language's distinctive advantages and charms. Many programmers who are familiar with a variety of languages frequently approach them from a constrained perspective rather than enjoying their full expressivity. Some programmers incorrectly use Programmatic features, which can later result in serious issues. The programmatic method of writing programs—the ideal approach to use programming languages—is explained in this book. This book is for all programmers, whether you are a novice or an experienced pro. Its numerous examples and well paced discussions will be especially beneficial for beginners. Those who are already familiar with programming will probably gain more from this book, of course. I want you to be prepared to use programming to make a big difference. "C, C++, Java, Python, PHP, JavaScript and Linux For Beginners" is a comprehensive guide to programming languages and operating systems for those who are new to the world of coding. This easy-to-follow book is designed to help readers learn the basics of programming and Linux operating system, and to gain confidence in their coding abilities. With clear and concise explanations, readers will be introduced to the fundamental concepts of programming languages such as C, C++, Java, Python, PHP, and JavaScript, as well as the basics of the Linux operating system. The book offers step-by-step guidance on how to write and execute code, along with practical exercises that help reinforce learning. Whether you are a student or a professional, "C, C++, Java, Python, PHP, JavaScript and Linux For Beginners" provides a solid foundation in programming and operating systems. By the end of this book, readers will have a solid understanding of the core concepts of programming and Linux, and will be equipped with the knowledge and skills to continue learning and exploring the exciting world of coding.
Book Synopsis THREE BOOKS IN ONE: Deep Learning Using SCIKIT-LEARN, KERAS, and TENSORFLOW with Python GUI by : Vivian Siahaan
Download or read book THREE BOOKS IN ONE: Deep Learning Using SCIKIT-LEARN, KERAS, and TENSORFLOW with Python GUI written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2021-05-20 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: BOOK 1: THE PRACTICAL GUIDES ON DEEP LEARNING USING SCIKIT-LEARN, KERAS, AND TENSORFLOW WITH PYTHON GUI In this book, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to implement deep learning on recognizing traffic signs using GTSRB dataset, detecting brain tumor using Brain Image MRI dataset, classifying gender, and recognizing facial expression using FER2013 dataset In Chapter 1, you will learn to create GUI applications to display line graph using PyQt. You will also learn how to display image and its histogram. In Chapter 2, you will learn how to use TensorFlow, Keras, Scikit-Learn, Pandas, NumPy and other libraries to perform prediction on handwritten digits using MNIST dataset with PyQt. You will build a GUI application for this purpose. In Chapter 3, you will learn how to perform recognizing traffic signs using GTSRB dataset from Kaggle. There are several different types of traffic signs like speed limits, no entry, traffic signals, turn left or right, children crossing, no passing of heavy vehicles, etc. Traffic signs classification is the process of identifying which class a traffic sign belongs to. In this Python project, you will build a deep neural network model that can classify traffic signs in image into different categories. With this model, you will be able to read and understand traffic signs which are a very important task for all autonomous vehicles. You will build a GUI application for this purpose. In Chapter 4, you will learn how to perform detecting brain tumor using Brain Image MRI dataset provided by Kaggle (https://www.kaggle.com/navoneel/brain-mri-images-for-brain-tumor-detection) using CNN model. You will build a GUI application for this purpose. In Chapter 5, you will learn how to perform classifying gender using dataset provided by Kaggle (https://www.kaggle.com/cashutosh/gender-classification-dataset) using MobileNetV2 and CNN models. You will build a GUI application for this purpose. In Chapter 6, you will learn how to perform recognizing facial expression using FER2013 dataset provided by Kaggle (https://www.kaggle.com/nicolejyt/facialexpressionrecognition) using CNN model. You will also build a GUI application for this purpose. BOOK 2: STEP BY STEP TUTORIALS ON DEEP LEARNING USING SCIKIT-LEARN, KERAS, AND TENSORFLOW WITH PYTHON GUI In this book, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to implement deep learning on classifying fruits, classifying cats/dogs, detecting furnitures, and classifying fashion. In Chapter 1, you will learn to create GUI applications to display line graph using PyQt. You will also learn how to display image and its histogram. Then, you will learn how to use OpenCV, NumPy, and other libraries to perform feature extraction with Python GUI (PyQt). The feature detection techniques used in this chapter are Harris Corner Detection, Shi-Tomasi Corner Detector, and Scale-Invariant Feature Transform (SIFT). In Chapter 2, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform classifying fruits using Fruits 360 dataset provided by Kaggle (https://www.kaggle.com/moltean/fruits/code) using Transfer Learning and CNN models. You will build a GUI application for this purpose. In Chapter 3, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform classifying cats/dogs using dataset provided by Kaggle (https://www.kaggle.com/chetankv/dogs-cats-images) using Using CNN with Data Generator. You will build a GUI application for this purpose. In Chapter 4, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform detecting furnitures using Furniture Detector dataset provided by Kaggle (https://www.kaggle.com/akkithetechie/furniture-detector) using VGG16 model. You will build a GUI application for this purpose. In Chapter 5, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform classifying fashion using Fashion MNIST dataset provided by Kaggle (https://www.kaggle.com/zalando-research/fashionmnist/code) using CNN model. You will build a GUI application for this purpose. BOOK 3: PROJECT-BASED APPROACH ON DEEP LEARNING USING SCIKIT-LEARN, KERAS, AND TENSORFLOW WITH PYTHON GUI In this book, implement deep learning on detecting vehicle license plates, recognizing sign language, and detecting surface crack using TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries. In Chapter 1, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform detecting vehicle license plates using Car License Plate Detection dataset provided by Kaggle (https://www.kaggle.com/andrewmvd/car-plate-detection/download). In Chapter 2, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform sign language recognition using Sign Language Digits Dataset provided by Kaggle (https://www.kaggle.com/ardamavi/sign-language-digits-dataset/download). In Chapter 3, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform detecting surface crack using Surface Crack Detection provided by Kaggle (https://www.kaggle.com/arunrk7/surface-crack-detection/download).
Book Synopsis Machine Learning with LightGBM and Python by : Andrich van Wyk
Download or read book Machine Learning with LightGBM and Python written by Andrich van Wyk and published by Packt Publishing Ltd. This book was released on 2023-09-29 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take your software to the next level and solve real-world data science problems by building production-ready machine learning solutions using LightGBM and Python Key Features Get started with LightGBM, a powerful gradient-boosting library for building ML solutions Apply data science processes to real-world problems through case studies Elevate your software by building machine learning solutions on scalable platforms Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMachine Learning with LightGBM and Python is a comprehensive guide to learning the basics of machine learning and progressing to building scalable machine learning systems that are ready for release. This book will get you acquainted with the high-performance gradient-boosting LightGBM framework and show you how it can be used to solve various machine-learning problems to produce highly accurate, robust, and predictive solutions. Starting with simple machine learning models in scikit-learn, you’ll explore the intricacies of gradient boosting machines and LightGBM. You’ll be guided through various case studies to better understand the data science processes and learn how to practically apply your skills to real-world problems. As you progress, you’ll elevate your software engineering skills by learning how to build and integrate scalable machine-learning pipelines to process data, train models, and deploy them to serve secure APIs using Python tools such as FastAPI. By the end of this book, you’ll be well equipped to use various -of-the-art tools that will help you build production-ready systems, including FLAML for AutoML, PostgresML for operating ML pipelines using Postgres, high-performance distributed training and serving via Dask, and creating and running models in the Cloud with AWS Sagemaker.What you will learn Get an overview of ML and working with data and models in Python using scikit-learn Explore decision trees, ensemble learning, gradient boosting, DART, and GOSS Master LightGBM and apply it to classification and regression problems Tune and train your models using AutoML with FLAML and Optuna Build ML pipelines in Python to train and deploy models with secure and performant APIs Scale your solutions to production readiness with AWS Sagemaker, PostgresML, and Dask Who this book is forThis book is for software engineers aspiring to be better machine learning engineers and data scientists unfamiliar with LightGBM, looking to gain in-depth knowledge of its libraries. Basic to intermediate Python programming knowledge is required to get started with the book. The book is also an excellent source for ML veterans, with a strong focus on ML engineering with up-to-date and thorough coverage of platforms such as AWS Sagemaker, PostgresML, and Dask.
Book Synopsis Linux Commands, C, C++, Java and Python Exercises For Beginners by : Manjunath.R
Download or read book Linux Commands, C, C++, Java and Python Exercises For Beginners written by Manjunath.R and published by Manjunath.R. This book was released on 2020-03-27 with total page 1453 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Hands-On Practice for Learning Linux and Programming Languages from Scratch" Are you new to Linux and programming? Do you want to learn Linux commands and programming languages like C, C++, Java, and Python but don't know where to start? Look no further! An approachable manual for new and experienced programmers that introduces the programming languages C, C++, Java, and Python. This book is for all programmers, whether you are a novice or an experienced pro. It is designed for an introductory course that provides beginning engineering and computer science students with a solid foundation in the fundamental concepts of computer programming. In this comprehensive guide, you will learn the essential Linux commands that every beginner should know, as well as gain practical experience with programming exercises in C, C++, Java, and Python. It also offers valuable perspectives on important computing concepts through the development of programming and problem-solving skills using the languages C, C++, Java, and Python. The beginner will find its carefully paced exercises especially helpful. Of course, those who are already familiar with programming are likely to derive more benefits from this book. After reading this book you will find yourself at a moderate level of expertise in C, C++, Java and Python, from which you can take yourself to the next levels. The command-line interface is one of the nearly all well built trademarks of Linux. There exists an ocean of Linux commands, permitting you to do nearly everything you can be under the impression of doing on your Linux operating system. However, this, at the end of time, creates a problem: because of all of so copious commands accessible to manage, you don't comprehend where and at which point to fly and learn them, especially when you are a learner. If you are facing this problem, and are peering for a painless method to begin your command line journey in Linux, you've come to the right place-as in this book, we will launch you to a hold of well liked and helpful Linux commands. This book gives a thorough introduction to the C, C++, Java, and Python programming languages, covering everything from fundamentals to advanced concepts. It also includes various exercises that let you put what you learn to use in the real world. With step-by-step instructions and plenty of examples, you'll build your knowledge and confidence in Linux and programming as you progress through the exercises. By the end of the book, you'll have a solid foundation in Linux commands and programming concepts, allowing you to take your skills to the next level. Whether you're a student, aspiring programmer, or curious hobbyist, this book is the perfect resource to start your journey into the exciting world of Linux and programming!
Book Synopsis SIX BOOKS IN ONE: Classification, Prediction, and Sentiment Analysis Using Machine Learning and Deep Learning with Python GUI by : Vivian Siahaan
Download or read book SIX BOOKS IN ONE: Classification, Prediction, and Sentiment Analysis Using Machine Learning and Deep Learning with Python GUI written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2022-04-11 with total page 1165 pages. Available in PDF, EPUB and Kindle. Book excerpt: Book 1: BANK LOAN STATUS CLASSIFICATION AND PREDICTION USING MACHINE LEARNING WITH PYTHON GUI The dataset used in this project consists of more than 100,000 customers mentioning their loan status, current loan amount, monthly debt, etc. There are 19 features in the dataset. The dataset attributes are as follows: Loan ID, Customer ID, Loan Status, Current Loan Amount, Term, Credit Score, Annual Income, Years in current job, Home Ownership, Purpose, Monthly Debt, Years of Credit History, Months since last delinquent, Number of Open Accounts, Number of Credit Problems, Current Credit Balance, Maximum Open Credit, Bankruptcies, and Tax Liens. The models used in this project are K-Nearest Neighbor, Random Forest, Naive Bayes, Logistic Regression, Decision Tree, Support Vector Machine, Adaboost, LGBM classifier, Gradient Boosting, and XGB classifier. Three feature scaling used in machine learning are raw, minmax scaler, and standard scaler. Finally, you will develop a GUI using PyQt5 to plot cross validation score, predicted values versus true values, confusion matrix, learning curve, decision boundaries, performance of the model, scalability of the model, training loss, and training accuracy. Book 2: OPINION MINING AND PREDICTION USING MACHINE LEARNING AND DEEP LEARNING WITH PYTHON GUI Opinion mining (sometimes known as sentiment analysis or emotion AI) refers to the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. This dataset was created for the Paper 'From Group to Individual Labels using Deep Features', Kotzias et. al,. KDD 2015. It contains sentences labelled with a positive or negative sentiment. Score is either 1 (for positive) or 0 (for negative). The sentences come from three different websites/fields: imdb.com, amazon.com, and yelp.com. For each website, there exist 500 positive and 500 negative sentences. Those were selected randomly for larger datasets of reviews. Amazon: contains reviews and scores for products sold on amazon.com in the cell phones and accessories category, and is part of the dataset collected by McAuley and Leskovec. Scores are on an integer scale from 1 to 5. Reviews considered with a score of 4 and 5 to be positive, and scores of 1 and 2 to be negative. The data is randomly partitioned into two halves of 50%, one for training and one for testing, with 35,000 documents in each set. IMDb: refers to the IMDb movie review sentiment dataset originally introduced by Maas et al. as a benchmark for sentiment analysis. This dataset contains a total of 100,000 movie reviews posted on imdb.com. There are 50,000 unlabeled reviews and the remaining 50,000 are divided into a set of 25,000 reviews for training and 25,000 reviews for testing. Each of the labeled reviews has a binary sentiment label, either positive or negative. Yelp: refers to the dataset from the Yelp dataset challenge from which we extracted the restaurant reviews. Scores are on an integer scale from 1 to 5. Reviews considered with scores 4 and 5 to be positive, and 1 and 2 to be negative. The data is randomly generated a 50-50 training and testing split, which led to approximately 300,000 documents for each set. Sentences: for each of the datasets above, labels are extracted and manually 1000 sentences are manually labeled from the test set, with 50% positive sentiment and 50% negative sentiment. These sentences are only used to evaluate our instance-level classifier for each dataset3. They are not used for model training, to maintain consistency with our overall goal of learning at a group level and predicting at the instance level. The models used in this project are K-Nearest Neighbor, Random Forest, Naive Bayes, Logistic Regression, Decision Tree, Support Vector Machine, Adaboost, LGBM classifier, Gradient Boosting, and XGB classifier. Three feature scaling used in machine learning are raw, minmax scaler, and standard scaler. Finally, you will develop a GUI using PyQt5 to plot cross validation score, predicted values versus true values, confusion matrix, learning curve, decision boundaries, performance of the model, scalability of the model, training loss, and training accuracy. Book 3: EMOTION PREDICTION FROM TEXT USING MACHINE LEARNING AND DEEP LEARNING WITH PYTHON GUI In the dataset used in this project, there are two columns, Text and Emotion. Quite self-explanatory. The Emotion column has various categories ranging from happiness to sadness to love and fear. You will build and implement machine learning and deep learning models which can identify what words denote what emotion. The models used in this project are K-Nearest Neighbor, Random Forest, Naive Bayes, Logistic Regression, Decision Tree, Support Vector Machine, Adaboost, LGBM classifier, Gradient Boosting, and XGB classifier. Three feature scaling used in machine learning are raw, minmax scaler, and standard scaler. Finally, you will develop a GUI using PyQt5 to plot cross validation score, predicted values versus true values, confusion matrix, learning curve, decision boundaries, performance of the model, scalability of the model, training loss, and training accuracy. Book 4: HATE SPEECH DETECTION AND SENTIMENT ANALYSIS USING MACHINE LEARNING AND DEEP LEARNING WITH PYTHON GUI The objective of this task is to detect hate speech in tweets. For the sake of simplicity, a tweet contains hate speech if it has a racist or sexist sentiment associated with it. So, the task is to classify racist or sexist tweets from other tweets. Formally, given a training sample of tweets and labels, where label '1' denotes the tweet is racist/sexist and label '0' denotes the tweet is not racist/sexist, the objective is to predict the labels on the test dataset. The models used in this project are K-Nearest Neighbor, Random Forest, Naive Bayes, Logistic Regression, Decision Tree, Support Vector Machine, Adaboost, LGBM classifier, Gradient Boosting, XGB classifier, LSTM, and CNN. Three feature scaling used in machine learning are raw, minmax scaler, and standard scaler. Finally, you will develop a GUI using PyQt5 to plot cross validation score, predicted values versus true values, confusion matrix, learning curve, decision boundaries, performance of the model, scalability of the model, training loss, and training accuracy. Book 5: TRAVEL REVIEW RATING CLASSIFICATION AND PREDICTION USING MACHINE LEARNING WITH PYTHON GUI The dataset used in this project has been sourced from the Machine Learning Repository of University of California, Irvine (UC Irvine): Travel Review Ratings Data Set. This dataset is populated by capturing user ratings from Google reviews. Reviews on attractions from 24 categories across Europe are considered. Google user rating ranges from 1 to 5 and average user rating per category is calculated. The attributes in the dataset are as follows: Attribute 1 : Unique user id; Attribute 2 : Average ratings on churches; Attribute 3 : Average ratings on resorts; Attribute 4 : Average ratings on beaches; Attribute 5 : Average ratings on parks; Attribute 6 : Average ratings on theatres; Attribute 7 : Average ratings on museums; Attribute 8 : Average ratings on malls; Attribute 9 : Average ratings on zoo; Attribute 10 : Average ratings on restaurants; Attribute 11 : Average ratings on pubs/bars; Attribute 12 : Average ratings on local services; Attribute 13 : Average ratings on burger/pizza shops; Attribute 14 : Average ratings on hotels/other lodgings; Attribute 15 : Average ratings on juice bars; Attribute 16 : Average ratings on art galleries; Attribute 17 : Average ratings on dance clubs; Attribute 18 : Average ratings on swimming pools; Attribute 19 : Average ratings on gyms; Attribute 20 : Average ratings on bakeries; Attribute 21 : Average ratings on beauty & spas; Attribute 22 : Average ratings on cafes; Attribute 23 : Average ratings on view points; Attribute 24 : Average ratings on monuments; and Attribute 25 : Average ratings on gardens. The models used in this project are K-Nearest Neighbor, Random Forest, Naive Bayes, Logistic Regression, Decision Tree, Support Vector Machine, Adaboost, LGBM classifier, Gradient Boosting, XGB classifier, and MLP classifier. Three feature scaling used in machine learning are raw, minmax scaler, and standard scaler. Finally, you will develop a GUI using PyQt5 to plot cross validation score, predicted values versus true values, confusion matrix, learning curve, decision boundaries, performance of the model, scalability of the model, training loss, and training accuracy. Book 6: ONLINE RETAIL CLUSTERING AND PREDICTION USING MACHINE LEARNING WITH PYTHON GUI The dataset used in this project is a transnational dataset which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail. The company mainly sells unique all-occasion gifts. Many customers of the company are wholesalers. You will be using the online retail transnational dataset to build a RFM clustering and choose the best set of customers which the company should target. In this project, you will perform Cohort analysis and RFM analysis. You will also perform clustering using K-Means to get 5 clusters. The machine learning models used in this project to predict clusters as target variable are K-Nearest Neighbor, Random Forest, Naive Bayes, Logistic Regression, Decision Tree, Support Vector Machine, LGBM, Gradient Boosting, XGB, and MLP. Finally, you will plot boundary decision, distribution of features, feature importance, cross validation score, and predicted values versus true values, confusion matrix, learning curve, performance of the model, scalability of the model, training loss, and training accuracy.
Book Synopsis The Book of Batch Scripting by : Jack McLarney
Download or read book The Book of Batch Scripting written by Jack McLarney and published by No Starch Press. This book was released on 2024-06-25 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: This fast-paced, hands-on, quirky introduction to Windows’ Batch scripting language is ideal for coders of all skill levels. In this era of advanced programming languages, the simplicity, universality, and efficiency of Batch scripting holds undeniable value. Whether you’re maintaining legacy systems or seeking to understand the foundations of command line automation, The Book of Batch Scripting shows you how to become proficient with this tool included in every version of Windows. As you work through the book, you will: Write a simple .bat file that performs a daily task with just a couple of mouse clicks Delve into variables and data types, and learn how a variable can possess two values at once—and why you should care Learn how to manage and collect data on files and directories either locally or on a network Harness the power of the for command to build complex loops with just a few lines of code Explore advanced topics like recursion, performing text searches, and even learn how to write a .bat file that writes a .bat file Extend Batch to use features like booleans, floats, operators, arrays, hash tables, stacks, queues, and even object-oriented design Written for beginners and experts alike, The Book of Batch Scripting will have you streamlining your workflow and writing effective code in no time. This simple but powerful tool is about to make your life a little bit easier and more fun. Requires: Microsoft Windows
Book Synopsis Two Books In One: LEARN FROM SCRATCH VISUAL BASIC .NET WITH MYSQL by : Vivian Siahaan
Download or read book Two Books In One: LEARN FROM SCRATCH VISUAL BASIC .NET WITH MYSQL written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2020-11-05 with total page 603 pages. Available in PDF, EPUB and Kindle. Book excerpt: BOOK 1: VISUAL BASIC .NET AND DATABASE: PRACTICAL TUTORIALS This book aims to develop a MySQL-driven desktop application that readers can develop for their own purposes to implement library project using Visual Basic .NET. In Tutorial 1, you will build a Visual Basic interface for the database. This interface will used as the main terminal in accessing other forms. This tutorial will also discuss how to create login form and login table. You will create login form. Place on the form one picture box, two labels, one combo box, one text box, and two buttons. In Tutorial 2, you will build a school inventory project where you can store information about valuables in school. The table will have nine fields: Item (description of the item), Quantity, Location (where the item was placed), Shop (where the item was purchased), DatePurchased (when the item was purchased), Cost (how much the item cost), SerialNumber (serial number of the item), PhotoFile (path of the photo file of the item), and Fragile (indicates whether a particular item is fragile or not). In Tutorial 3, you will perform the steps necessary to add 5 new tables using phpMyAdmin into Academy database. You will build each table and add the associated fields as needed. Every table in the database will need input form. In this tutorial, you will build such a form for Author table. Although this table is quite simple (only four fields: AuthorID, Name, BirthDate, and PhotoFile), it provides a basis for illustrating the many steps in interface design. SQL statement is required by the Command object to read fields (sorted by Name). Then, you will build an interface so that the user can maintain the Publisher table in the database (Academy). The Publisher table interface is more or less the same as Author table interface. This Publisher table interface only requires more input fields. So you will use the interface for the Author table and modify it for the Publisher table. In Tutorial 4, you will perform the steps necessary to design and implement title form, library member form, and book borrowal form. You start by designing and testing the basic entry form for book titles. The Title table has nine fields: BookTitle, PublishYear, ISBN, PublisherID, AuthorID, Description, Note, Subject, and Comment. Then, you will build such a form for Member table. This table has twelve fields: MemberID, FirstName, LastName, BirthDate, Status, Ethnicity, Nationality, Mobile, Phone, Religion, Gender, and PhotoFile). You need thirteen label controls, one picture box, six text boxes, four comboxes, one check box, one date time picker, one openfiledialog, and one printpreviewdialog. You also need four buttons for navigation, six buttons for controlling editing features, one button for searching member’s name, and one button to upload member’s photo. Finally, you will build such a form for Borrow table. This table has seven fields: BorrowID, MemberID, BorrowCode, ISBN, BorrowDate, ReturnDate, and Penalty. In this form, you need fourteen label controls, seven text boxes, two comboxes, two date time pickers, and one printpreviewdialog. You also need four buttons for navigation, seven buttons for other utilities, one button to generate borrowal code, and one button to return book. BOOK 2: LEARN FROM SCRATCH VISUAL BASIC .NET WITH MYSQL This book will teach you with step-by-step approach to develop from scratch a MySQL-driven desktop application that readers can develop for their own purposes to implement school database project using Visual Basic .NET. In Tutorial 1, you will perform the steps necessary to add 8 tables using phpMyAdmin into School database that you will create. You will build each table and add the associated fields as needed. In this tutorial, you will also build login form and main form. In Tutorial 2, you will build such a form for Parent table. This table has thirteen fields: ParentID, FirstName, LastName, BirthDate, Status, Ethnicity, Nationality, Mobile, Phone, Religion, Gender, PhotoFile, and FingerFile). You need fourteen label controls, two picture boxes, six text boxes, four comboxes, one check box, one date time picker, one openfiledialog, and one printpreviewdialog. You also need four buttons for navigation, six buttons for other utilities, one button for searching member’s name, one button to upload parent’s photo, and button to upload parent’s finger. Place these controls on the form. In Tutorial 3, you will build such a form for Student table. This table has fifteen fields: StudentID, ParentID, FirstName, LastName, BirthDate, YearEntry, Status, Ethnicity, Nationality, Mobile, Phone, Religion, Gender, PhotoFile, and FingerFile). You need sixteen label controls, two picture boxes, six text boxes, five comboxes, one check box, two date time pickers, one openfiledialog, and one printpreviewdialog. You also need four buttons for navigation, seven buttons for controlling editing features, one button for searching parent’s name, one button to open parent form, one button to upload student’s photo, and one button to upload student’s finger. In Tutorial 4, you will build a form for Teacher table. This table has fifteen fields: TeacherID, RegNumber, FirstName, LastName, BirthDate, Rank, Status, Ethnicity, Nationality, Mobile, Phone, Religion, Gender, PhotoFile, and FingerFile). You need an input form so that user can edit existing records, delete records, or add new records. The form will also have the capability of navigating from one record to another. You need sixteen label controls, one picture box, seven text boxes, five comboxes, one check box, one date time picker, one openfiledialog, and one printpreviewdialog. You also need four buttons for navigation, six buttons for controlling editing features, one button for searching teacher’s name, and one button to upload teacher’s photo. In Tutorial 5, you will build a form for Subject table. This table has only three fields: SubjectID, Name, and Description. You need four label controls, four text boxes, one openfiledialog, and one printpreviewdialog. You also need four buttons for navigation, secen buttons for utilities, and one button for searching subject name. Place these controls on the form. You will also build a form for Grade table. This table has seven fields: GradeID, Name, SubjectID, TeacherID, SchoolYear, TimaStart, and TimeFinish. You need to add seven label controls, one text box, four comboxes, and two date time pickers. You also need four buttons for navigation, seven buttons for controlling editing features, one button to open subject form, and one button to open teacher form. In Tutorial 6, you will build a form for Grade_Student table. This table has only three fields: Grade_StudentID, GradeID, and StudentID. You need an input form so that user can edit existing records, delete records, or add new records. The form will also have the capability of navigating from one record to another. You need two label controls and two comboxes. You also need four buttons for navigation, seven buttons for controlling editing features, one button to open grade form, and one button to open student form.
Book Synopsis Python All-in-One For Dummies by : John C. Shovic
Download or read book Python All-in-One For Dummies written by John C. Shovic and published by John Wiley & Sons. This book was released on 2019-05-07 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: Your one-stop resource on all things Python Thanks to its flexibility, Python has grown to become one of the most popular programming languages in the world. Developers use Python in app development, web development, data science, machine learning, and even in coding education classes. There's almost no type of project that Python can't make better. From creating apps to building complex websites to sorting big data, Python provides a way to get the work done. Python All-in-One For Dummies offers a starting point for those new to coding by explaining the basics of Python and demonstrating how it’s used in a variety of applications. Covers the basics of the language Explains its syntax through application in high-profile industries Shows how Python can be applied to projects in enterprise Delves into major undertakings including artificial intelligence, physical computing, machine learning, robotics and data analysis This book is perfect for anyone new to coding as well as experienced coders interested in adding Python to their toolbox.
