Python For Data Mining Quick Syntax Reference

Download Python For Data Mining Quick Syntax Reference full books in PDF, epub, and Kindle. Read online Python For Data Mining Quick Syntax Reference ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Python for Data Mining Quick Syntax Reference

Author : Valentina Porcu
Publisher : Apress
ISBN 13 : 1484241134
Total Pages : 269 pages
Book Rating : 4.4/5 (842 download)

DOWNLOAD NOW!

Book Synopsis Python for Data Mining Quick Syntax Reference by : Valentina Porcu

Download or read book Python for Data Mining Quick Syntax Reference written by Valentina Porcu and published by Apress. This book was released on 2018-12-19 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use Python and its structures, how to install Python, and which tools are best suited for data analyst work. This book provides you with a handy reference and tutorial on topics ranging from basic Python concepts through to data mining, manipulating and importing datasets, and data analysis. Python for Data Mining Quick Syntax Reference covers each concept concisely, with many illustrative examples. You'll be introduced to several data mining packages, with examples of how to use each of them. The first part covers core Python including objects, lists, functions, modules, and error handling. The second part covers Python's most important data mining packages: NumPy and SciPy for mathematical functions and random data generation, pandas for dataframe management and data import, Matplotlib for drawing charts, and scikitlearn for machine learning. What You'll LearnInstall Python and choose a development environment Understand the basic concepts of object-oriented programming Import, open, and edit files Review the differences between Python 2.x and 3.xWho This Book Is For Programmers new to Python's data mining packages or with experience in other languages, who want a quick guide to Pythonic tools and techniques.

Python Data Mining Quick Start Guide

Author : Nathan Greeneltch
Publisher : Packt Publishing Ltd
ISBN 13 : 1789806402
Total Pages : 181 pages
Book Rating : 4.7/5 (898 download)

DOWNLOAD NOW!

Book Synopsis Python Data Mining Quick Start Guide by : Nathan Greeneltch

Download or read book Python Data Mining Quick Start Guide written by Nathan Greeneltch and published by Packt Publishing Ltd. This book was released on 2019-04-25 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the different data mining techniques using the libraries and packages offered by Python Key FeaturesGrasp the basics of data loading, cleaning, analysis, and visualizationUse the popular Python libraries such as NumPy, pandas, matplotlib, and scikit-learn for data miningYour one-stop guide to build efficient data mining pipelines without going into too much theoryBook Description Data mining is a necessary and predictable response to the dawn of the information age. It is typically defined as the pattern and/ or trend discovery phase in the data mining pipeline, and Python is a popular tool for performing these tasks as it offers a wide variety of tools for data mining. This book will serve as a quick introduction to the concept of data mining and putting it to practical use with the help of popular Python packages and libraries. You will get a hands-on demonstration of working with different real-world datasets and extracting useful insights from them using popular Python libraries such as NumPy, pandas, scikit-learn, and matplotlib. You will then learn the different stages of data mining such as data loading, cleaning, analysis, and visualization. You will also get a full conceptual description of popular data transformation, clustering, and classification techniques. By the end of this book, you will be able to build an efficient data mining pipeline using Python without any hassle. What you will learnExplore the methods for summarizing datasets and visualizing/plotting dataCollect and format data for analytical workAssign data points into groups and visualize clustering patternsLearn how to predict continuous and categorical outputs for dataClean, filter noise from, and reduce the dimensions of dataSerialize a data processing model using scikit-learn’s pipeline featureDeploy the data processing model using Python’s pickle moduleWho this book is for Python developers interested in getting started with data mining will love this book. Budding data scientists and data analysts looking to quickly get to grips with practical data mining with Python will also find this book to be useful. Knowledge of Python programming is all you need to get started.

Julia Quick Syntax Reference

Author : Antonello Lobianco
Publisher : Apress
ISBN 13 : 1484251903
Total Pages : 223 pages
Book Rating : 4.4/5 (842 download)

DOWNLOAD NOW!

Book Synopsis Julia Quick Syntax Reference by : Antonello Lobianco

Download or read book Julia Quick Syntax Reference written by Antonello Lobianco and published by Apress. This book was released on 2019-11-11 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: This quick Julia programming language guide is a condensed code and syntax reference to the Julia 1.x programming language, updated with the latest features of the Julia APIs, libraries, and packages. It presents the essential Julia syntax in a well-organized format that can be used as a handy reference. This book provides an introduction that reveals basic Julia structures and syntax; discusses data types, control flow, functions, input/output, exceptions, metaprogramming, performance, and more. Additionally, you'll learn to interface Julia with other programming languages such as R for statistics or Python. You will learn how to use Julia packages for data analysis, numerical optimization and symbolic computation, and how to disseminate your results in dynamic documents or interactive web pages. In this book, the focus is on providing important information as quickly as possible. It is packed with useful information and is a must-have for any Julia programmer. What You Will Learn Set up the software needed to run Julia and your first Hello World exampleWork with types and the different containers that Julia makes available for rapid application developmentUse vectorized, classical loop-based code, logical operators, and blocksExplore Julia functions by looking at arguments, return values, polymorphism, parameters, anonymous functions, and broadcastsBuild custom structures in JuliaInterface Julia with other languages such as C/C++, Python, and RProgram a richer API, modifying the code before it is executed using expressions, symbols, macros, quote blocks, and moreMaximize your code’s performance Who This Book Is For Experienced programmers new to Julia, as well as existing Julia coders new to the now stable Julia version 1.0 release.

The Python Quick Syntax Reference

Author : Gregory Walters
Publisher : Apress
ISBN 13 : 1430264799
Total Pages : 140 pages
Book Rating : 4.4/5 (32 download)

DOWNLOAD NOW!

Book Synopsis The Python Quick Syntax Reference by : Gregory Walters

Download or read book The Python Quick Syntax Reference written by Gregory Walters and published by Apress. This book was released on 2014-02-28 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Python Quick Syntax Reference is the "go to" book that contains an easy to read and use guide to Python programming and development. This condensed code and syntax reference presents the Python language in a well-organized format designed to be used time and again. You won't find jargon, bloated samples, case studies, or history of Hello World and computer theory in this handy reference. This Python syntax reference is packed with useful information and is a must-have for any Python developer.

Learning Data Mining with Python

Author : Robert Layton
Publisher : Packt Publishing Ltd
ISBN 13 : 1784391204
Total Pages : 344 pages
Book Rating : 4.7/5 (843 download)

DOWNLOAD NOW!

Book Synopsis Learning Data Mining with Python by : Robert Layton

Download or read book Learning Data Mining with Python written by Robert Layton and published by Packt Publishing Ltd. This book was released on 2015-07-29 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: The next step in the information age is to gain insights from the deluge of data coming our way. Data mining provides a way of finding this insight, and Python is one of the most popular languages for data mining, providing both power and flexibility in analysis. This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. Next, we move on to more complex data types including text, images, and graphs. In every chapter, we create models that solve real-world problems. There is a rich and varied set of libraries available in Python for data mining. This book covers a large number, including the IPython Notebook, pandas, scikit-learn and NLTK. Each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will gain a large insight into using Python for data mining, with a good knowledge and understanding of the algorithms and implementations.

Mathematics and Computer Science, Volume 1

Author : Sharmistha Ghosh
Publisher : John Wiley & Sons
ISBN 13 : 1119879817
Total Pages : 564 pages
Book Rating : 4.1/5 (198 download)

DOWNLOAD NOW!

Book Synopsis Mathematics and Computer Science, Volume 1 by : Sharmistha Ghosh

Download or read book Mathematics and Computer Science, Volume 1 written by Sharmistha Ghosh and published by John Wiley & Sons. This book was released on 2023-07-19 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: MATHEMATICS AND COMPUTER SCIENCE This first volume in a new multi-volume set gives readers the basic concepts and applications for diverse ideas and innovations in the field of computing together with its growing interactions with mathematics. This new edited volume from Wiley-Scrivener is the first of its kind to present scientific and technological innovations by leading academicians, eminent researchers, and experts around the world in the areas of mathematical sciences and computing. The chapters focus on recent advances in computer science, and mathematics, and where the two intersect to create value for end users through practical applications of the theory. The chapters herein cover scientific advancements across a diversified spectrum that includes differential as well as integral equations with applications, computational fluid dynamics, nanofluids, network theory and optimization, control theory, machine learning and artificial intelligence, big data analytics, Internet of Things, cryptography, fuzzy automata, statistics, and many more. Readers of this book will get access to diverse ideas and innovations in the field of computing together with its growing interactions in various fields of mathematics. Whether for the engineer, scientist, student, academic, or other industry professional, this is a must-have for any library.

Applications of Evolutionary Computation

Author : Juan Luis Jiménez Laredo
Publisher : Springer Nature
ISBN 13 : 3031024621
Total Pages : 759 pages
Book Rating : 4.0/5 (31 download)

DOWNLOAD NOW!

Book Synopsis Applications of Evolutionary Computation by : Juan Luis Jiménez Laredo

Download or read book Applications of Evolutionary Computation written by Juan Luis Jiménez Laredo and published by Springer Nature. This book was released on 2022-04-15 with total page 759 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 25th International Conference on Applications of Evolutionary Computation, EvoApplications 2022, held as part of Evo*2022, in April 2022, co-located with the Evo*2022 events EuroGP, EvoCOP, and EvoMUSART. The 46 revised full papers presented in this book were carefully reviewed and selected from 67 submissions.

Handbook of Research on Technological Advances of Library and Information Science in Industry 5.0

Author : Holland, Barbara Jane
Publisher : IGI Global
ISBN 13 : 1668447568
Total Pages : 584 pages
Book Rating : 4.6/5 (684 download)

DOWNLOAD NOW!

Book Synopsis Handbook of Research on Technological Advances of Library and Information Science in Industry 5.0 by : Holland, Barbara Jane

Download or read book Handbook of Research on Technological Advances of Library and Information Science in Industry 5.0 written by Holland, Barbara Jane and published by IGI Global. This book was released on 2022-12-29 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: Industry 5.0 is advancing the collaboration between humans and machines and is finding value through connected virtual and human experiences. This technological revolution benefits numerous fields; however, the library and information science industry in particular can evolve and expand by embracing Industry 5.0. The Handbook of Research on Technological Advances of Library and Information Science in Industry 5.0 considers the current research and future trends of technological advances in library and information science related to Industry 5.0. Covering key topics such as robotics, smart libraries, augmented reality, digital libraries, and artificial intelligence, this major reference work is ideal for librarians, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.

Learn By Examples - A Quick Guide To Data Science With Python

Author : Eric M. H. Goh
Publisher : SVBook Pte. Ltd.
ISBN 13 : 1635352991
Total Pages : 101 pages
Book Rating : 4.6/5 (353 download)

DOWNLOAD NOW!

Book Synopsis Learn By Examples - A Quick Guide To Data Science With Python by : Eric M. H. Goh

Download or read book Learn By Examples - A Quick Guide To Data Science With Python written by Eric M. H. Goh and published by SVBook Pte. Ltd. . This book was released on with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aim to equip the reader with Python Programming and Data Science basics. There will be many examples and explanations that are straight to the point. You will be walked through data mining process from data preparation to data analysis (descriptive statistics) and data visualization to prediction modeling (machine learning) and deployment using Python. Content Covered: IntroductionGetting Started (Installing WinPython, IDE, ...)Language Essentials (variables, list, data types manipulations, ...)Language Essentials II (conditional statements, loops, ...)Object Essentials (Modules, Class and Objects, ...)Data Mining with Python (Pandas, ScikitLearn, ...) We will be using opensource tools and IDE, hence, you don't have to worry about buying any softwares. The book is designed for non-programmers only. It will gives you a head start into python programming, with a touch on data mining. This book has been taught at Udemy and EMHAcademy.com. Use the following Coupon to get the Udemy Course at $11.99: https://www.udemy.com/fundamentals-of-python-for-data-mining/?couponCode=EBOOKSPECIAL ISBN: 978-163535299-3

Python Data Analytics

Author : Fabio Nelli
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (114 download)

DOWNLOAD NOW!

Book Synopsis Python Data Analytics by : Fabio Nelli

Download or read book Python Data Analytics written by Fabio Nelli and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Python Data Analytics will help you tackle the world of data acquisition and analysis using the power of the Python language. At the heart of this book lies the coverage of pandas, an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. Author Fabio Nelli expertly shows the strength of the Python programming language when applied to processing, managing and retrieving information. Inside, you will see how intuitive and flexible it is to discover and communicate meaningful patterns of data using Python scripts, reporting systems, and data export. This book examines how to go about obtaining, processing, storing, managing and analyzing data using the Python programming language. You will use Python and other open source tools to wrangle data and tease out interesting and important trends in that data that will allow you to predict future patterns. Whether you are dealing with sales data, investment data (stocks, bonds, etc.), medical data, web page usage, or any other type of data set, Python can be used to interpret, analyze, and glean information from a pile of numbers and statistics. This book is an invaluable reference with its examples of storing and accessing data in a database; it walks you through the process of report generation; it provides three real world case studies or examples that you can take with you for your everyday analysis needs.

Getting Started with Python Data Analysis

Author : Phuong Vo.T.H
Publisher : Packt Publishing Ltd
ISBN 13 : 1783988452
Total Pages : 188 pages
Book Rating : 4.7/5 (839 download)

DOWNLOAD NOW!

Book Synopsis Getting Started with Python Data Analysis by : Phuong Vo.T.H

Download or read book Getting Started with Python Data Analysis written by Phuong Vo.T.H and published by Packt Publishing Ltd. This book was released on 2015-11-04 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to use powerful Python libraries for effective data processing and analysis About This Book Learn the basic processing steps in data analysis and how to use Python in this area through supported packages, especially Numpy, Pandas, and Matplotlib Create, manipulate, and analyze your data to extract useful information to optimize your system A hands-on guide to help you learn data analysis using Python Who This Book Is For If you are a Python developer who wants to get started with data analysis and you need a quick introductory guide to the python data analysis libraries, then this book is for you. What You Will Learn Understand the importance of data analysis and get familiar with its processing steps Get acquainted with Numpy to use with arrays and array-oriented computing in data analysis Create effective visualizations to present your data using Matplotlib Process and analyze data using the time series capabilities of Pandas Interact with different kind of database systems, such as file, disk format, Mongo, and Redis Apply the supported Python package to data analysis applications through examples Explore predictive analytics and machine learning algorithms using Scikit-learn, a Python library In Detail Data analysis is the process of applying logical and analytical reasoning to study each component of data. Python is a multi-domain, high-level, programming language. It's often used as a scripting language because of its forgiving syntax and operability with a wide variety of different eco-systems. Python has powerful standard libraries or toolkits such as Pylearn2 and Hebel, which offers a fast, reliable, cross-platform environment for data analysis. With this book, we will get you started with Python data analysis and show you what its advantages are. The book starts by introducing the principles of data analysis and supported libraries, along with NumPy basics for statistic and data processing. Next it provides an overview of the Pandas package and uses its powerful features to solve data processing problems. Moving on, the book takes you through a brief overview of the Matplotlib API and some common plotting functions for DataFrame such as plot. Next, it will teach you to manipulate the time and data structure, and load and store data in a file or database using Python packages. The book will also teach you how to apply powerful packages in Python to process raw data into pure and helpful data using examples. Finally, the book gives you a brief overview of machine learning algorithms, that is, applying data analysis results to make decisions or build helpful products, such as recommendations and predictions using scikit-learn. Style and approach This is an easy-to-follow, step-by-step guide to get you familiar with data analysis and the libraries supported by Python. Topics are explained with real-world examples wherever required.

Python Data Science Handbook

Author : Jake VanderPlas
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491912138
Total Pages : 743 pages
Book Rating : 4.4/5 (919 download)

DOWNLOAD NOW!

Book Synopsis Python Data Science Handbook by : Jake VanderPlas

Download or read book Python Data Science Handbook written by Jake VanderPlas and published by "O'Reilly Media, Inc.". This book was released on 2016-11-21 with total page 743 pages. Available in PDF, EPUB and Kindle. Book excerpt: For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

Python Data Analysis Cookbook

Author : Ivan Idris
Publisher : Packt Publishing Ltd
ISBN 13 : 1785283855
Total Pages : 462 pages
Book Rating : 4.7/5 (852 download)

DOWNLOAD NOW!

Book Synopsis Python Data Analysis Cookbook by : Ivan Idris

Download or read book Python Data Analysis Cookbook written by Ivan Idris and published by Packt Publishing Ltd. This book was released on 2016-07-22 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 140 practical recipes to help you make sense of your data with ease and build production-ready data apps About This Book Analyze Big Data sets, create attractive visualizations, and manipulate and process various data types Packed with rich recipes to help you learn and explore amazing algorithms for statistics and machine learning Authored by Ivan Idris, expert in python programming and proud author of eight highly reviewed books Who This Book Is For This book teaches Python data analysis at an intermediate level with the goal of transforming you from journeyman to master. Basic Python and data analysis skills and affinity are assumed. What You Will Learn Set up reproducible data analysis Clean and transform data Apply advanced statistical analysis Create attractive data visualizations Web scrape and work with databases, Hadoop, and Spark Analyze images and time series data Mine text and analyze social networks Use machine learning and evaluate the results Take advantage of parallelism and concurrency In Detail Data analysis is a rapidly evolving field and Python is a multi-paradigm programming language suitable for object-oriented application development and functional design patterns. As Python offers a range of tools and libraries for all purposes, it has slowly evolved as the primary language for data science, including topics on: data analysis, visualization, and machine learning. Python Data Analysis Cookbook focuses on reproducibility and creating production-ready systems. You will start with recipes that set the foundation for data analysis with libraries such as matplotlib, NumPy, and pandas. You will learn to create visualizations by choosing color maps and palettes then dive into statistical data analysis using distribution algorithms and correlations. You'll then help you find your way around different data and numerical problems, get to grips with Spark and HDFS, and then set up migration scripts for web mining. In this book, you will dive deeper into recipes on spectral analysis, smoothing, and bootstrapping methods. Moving on, you will learn to rank stocks and check market efficiency, then work with metrics and clusters. You will achieve parallelism to improve system performance by using multiple threads and speeding up your code. By the end of the book, you will be capable of handling various data analysis techniques in Python and devising solutions for problem scenarios. Style and Approach The book is written in “cookbook” style striving for high realism in data analysis. Through the recipe-based format, you can read each recipe separately as required and immediately apply the knowledge gained.

"Numerical Methods using Python (For scientists and Engineers)"

Author : Pankaj Dumka
Publisher : Blue Rose Publishers
ISBN 13 :
Total Pages : 128 pages
Book Rating : 4./5 ( download)

DOWNLOAD NOW!

Book Synopsis "Numerical Methods using Python (For scientists and Engineers)" by : Pankaj Dumka

Download or read book "Numerical Methods using Python (For scientists and Engineers)" written by Pankaj Dumka and published by Blue Rose Publishers. This book was released on 2022-11-21 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is specifically intended for scientists, engineers, and engineering students who have taken a course on numeric methods and wish to comprehend and learn the subject through programming. The book's chapters are written methodically (step-by-step) so that programming becomes simple. More emphasis is placed on computationally modelling the methodologies and discussing the numerical method. Python is chosen as the programming language because it is simple to comprehend and use compared to other programming languages. The book allows readers to use and experiment with the approaches it describes. With very few adjustments, many of the programmes in the book can be utilised for applications in science and engineering.

Learning Data Mining with Python

Author : Robert Layton
Publisher : Packt Publishing Ltd
ISBN 13 : 178712956X
Total Pages : 348 pages
Book Rating : 4.7/5 (871 download)

DOWNLOAD NOW!

Book Synopsis Learning Data Mining with Python by : Robert Layton

Download or read book Learning Data Mining with Python written by Robert Layton and published by Packt Publishing Ltd. This book was released on 2017-04-27 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Harness the power of Python to develop data mining applications, analyze data, delve into machine learning, explore object detection using Deep Neural Networks, and create insightful predictive models. About This Book Use a wide variety of Python libraries for practical data mining purposes. Learn how to find, manipulate, analyze, and visualize data using Python. Step-by-step instructions on data mining techniques with Python that have real-world applications. Who This Book Is For If you are a Python programmer who wants to get started with data mining, then this book is for you. If you are a data analyst who wants to leverage the power of Python to perform data mining efficiently, this book will also help you. No previous experience with data mining is expected. What You Will Learn Apply data mining concepts to real-world problems Predict the outcome of sports matches based on past results Determine the author of a document based on their writing style Use APIs to download datasets from social media and other online services Find and extract good features from difficult datasets Create models that solve real-world problems Design and develop data mining applications using a variety of datasets Perform object detection in images using Deep Neural Networks Find meaningful insights from your data through intuitive visualizations Compute on big data, including real-time data from the internet In Detail This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. This book covers a large number of libraries available in Python, including the Jupyter Notebook, pandas, scikit-learn, and NLTK. You will gain hands on experience with complex data types including text, images, and graphs. You will also discover object detection using Deep Neural Networks, which is one of the big, difficult areas of machine learning right now. With restructured examples and code samples updated for the latest edition of Python, each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will have great insights into using Python for data mining and understanding of the algorithms as well as implementations. Style and approach This book will be your comprehensive guide to learning the various data mining techniques and implementing them in Python. A variety of real-world datasets is used to explain data mining techniques in a very crisp and easy to understand manner.

Python Data Science

Author : Christopher Wilkinson
Publisher :
ISBN 13 : 9781702806206
Total Pages : 202 pages
Book Rating : 4.8/5 (62 download)

DOWNLOAD NOW!

Book Synopsis Python Data Science by : Christopher Wilkinson

Download or read book Python Data Science written by Christopher Wilkinson and published by . This book was released on 2019-10-26 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Ultimate Guide to Learn Fundamentals of Python Data Science is full of insights and strategies for data scientists, programming professionals, and students who want to equip themselves with the new trending libraries and functions of Python as a data management tool. This book has all the major techniques of data collection, interpretation and processing to achieve refined information. The reader will learn about the scientific research of data, syntax of Python programming language, and all the basic knowledge of imported libraries and methods.An effective approach of Python data science can save time, resources, and energy. You can learn to help any company with the running processes: accounts, HR modules, sales, services and more. Keeping in view the requirements of brand and competition, this guide for beginners covers all the data management strategies and tactics. The development of the well-structured function of Python is purely a systematic and knowledge-based technique. Building a scientific data research system has never been as easy as it is today. A lot of companies have shifted their data systems to the open-source, easy to learn, Python language. If you really want to learn Python Data Science, don't waste your time looking around - buy this extraordinary book now to get started. It is a detailed book with a comprehensive knowledge of data science, Python data structures, standard libraries, data science frameworks and predictive models in Python. Build your success story through learning the best practices of data science. Click the Buy button to get started.

Python for Data Science

Author : Oscar Brogan
Publisher :
ISBN 13 :
Total Pages : 156 pages
Book Rating : 4.6/5 (23 download)

DOWNLOAD NOW!

Book Synopsis Python for Data Science by : Oscar Brogan

Download or read book Python for Data Science written by Oscar Brogan and published by . This book was released on 2020-03-09 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you a new business owner? Or an entrepreneur looking to catch up to the big companies in your industrial sector? Do you want to find new solutions for complex decisions and maybe automate the entire process? Don't worry: background in coding language is not required! This is the book you need to understand and master the fundamentals and importance of data science technologies to kick start your business or take it to the next level. Thanks to the smart and savvy customers of today, the competition to gain new customers while retaining existing customers is fierce. As a result, companies are increasingly relying upon cutting edge technologies such as big data analytics, data mining technology, machine learning, and artificial intelligence technology to gain an edge over the competition Today machine learning and artificial intelligence have given rise to sophisticated machines that can study human behavior and activity to identify underlying human behavioral patterns and precisely predict what products and services consumers are interested in. Businesses with an eye on the future are gradually turning into technology companies under the façade of their intended business model. It is getting increasingly challenging for traditional businesses to retain their customers without adopting one or more of the cutting-edge technology explained in this book. Those entrepreneurs and business executives who have a sound understanding of the current challenges and status of their business will be primed to make informed decisions to meet the challenges head-on and improve their bottom line. This is where the treasure trove of knowledge from this book will help you take an exciting new turn on your business journey and compete with the titans of the Silicon Valley. Do you found only complicated books? Don't worry You will find an easy-to-follow guide with the complex concepts explained easily. Some of the highlights of the book include: Learn the nuances of "12 of the most popular machine learning algorithms", in a very easy to understand language that requires no background in Python coding language Learn about the foundational machine learning algorithms namely, supervised, unsupervised, semi-supervised, and reinforcement machine learning algorithms Explicit list of all built-in Python functions, methods, and keywords that can be used to easily develop and run advanced codes Learn how Python programming is being used in the development and testing of software programs and machine learning algorithms to solve real-world problems Learn all about big data right from the historical development to the current explosion in this field Dig deep into the data mining process, the benefits of using data mining technology, the challenges facing the data mining technology Deep dive into the functioning of Scikit-Learn library along with the pre-requisites required to develop a machine learning model using the Scikit-Learn library and many more... This book is filled with real-life examples to help you understand the nitty-gritty of all the concepts as well as names and descriptions of multiple tools that you can further explore and selectively implement in your business to reap the benefits of these cutting-edge technologies. Remember knowledge is power, and with the great power you will gather from this book, you will be armed to make sound personal and professional technological choices. This is a must-have Python guide, and with this book, you can boost your knowledge and master big data and analytics with this easy-to-follow technique. Scroll up and hit that BUY BUTTON!