Machine Learning For Beginners Guide Algorithms

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Machine Learning Algorithms

Author : Giuseppe Bonaccorso
Publisher : Packt Publishing Ltd
ISBN 13 : 1785884514
Total Pages : 360 pages
Book Rating : 4.7/5 (858 download)

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Book Synopsis Machine Learning Algorithms by : Giuseppe Bonaccorso

Download or read book Machine Learning Algorithms written by Giuseppe Bonaccorso and published by Packt Publishing Ltd. This book was released on 2017-07-24 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide About This Book Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide. Your one-stop solution for everything that matters in mastering the whats and whys of Machine Learning algorithms and their implementation. Get a solid foundation for your entry into Machine Learning by strengthening your roots (algorithms) with this comprehensive guide. Who This Book Is For This book is for IT professionals who want to enter the field of data science and are very new to Machine Learning. Familiarity with languages such as R and Python will be invaluable here. What You Will Learn Acquaint yourself with important elements of Machine Learning Understand the feature selection and feature engineering process Assess performance and error trade-offs for Linear Regression Build a data model and understand how it works by using different types of algorithm Learn to tune the parameters of Support Vector machines Implement clusters to a dataset Explore the concept of Natural Processing Language and Recommendation Systems Create a ML architecture from scratch. In Detail As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of Big Data and Data Science. The main challenge is how to transform data into actionable knowledge. In this book you will learn all the important Machine Learning algorithms that are commonly used in the field of data science. These algorithms can be used for supervised as well as unsupervised learning, reinforcement learning, and semi-supervised learning. A few famous algorithms that are covered in this book are Linear regression, Logistic Regression, SVM, Naive Bayes, K-Means, Random Forest, TensorFlow, and Feature engineering. In this book you will also learn how these algorithms work and their practical implementation to resolve your problems. This book will also introduce you to the Natural Processing Language and Recommendation systems, which help you run multiple algorithms simultaneously. On completion of the book you will have mastered selecting Machine Learning algorithms for clustering, classification, or regression based on for your problem. Style and approach An easy-to-follow, step-by-step guide that will help you get to grips with real -world applications of Algorithms for Machine Learning.

Machine Learning For Dummies

Author : John Paul Mueller
Publisher : John Wiley & Sons
ISBN 13 : 1119724015
Total Pages : 471 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Machine Learning For Dummies by : John Paul Mueller

Download or read book Machine Learning For Dummies written by John Paul Mueller and published by John Wiley & Sons. This book was released on 2021-02-09 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of Mark Cuban’s top reads for better understanding A.I. (inc.com, 2021) Your comprehensive entry-level guide to machine learning While machine learning expertise doesn’t quite mean you can create your own Turing Test-proof android—as in the movie Ex Machina—it is a form of artificial intelligence and one of the most exciting technological means of identifying opportunities and solving problems fast and on a large scale. Anyone who masters the principles of machine learning is mastering a big part of our tech future and opening up incredible new directions in careers that include fraud detection, optimizing search results, serving real-time ads, credit-scoring, building accurate and sophisticated pricing models—and way, way more. Unlike most machine learning books, the fully updated 2nd Edition of Machine Learning For Dummies doesn't assume you have years of experience using programming languages such as Python (R source is also included in a downloadable form with comments and explanations), but lets you in on the ground floor, covering the entry-level materials that will get you up and running building models you need to perform practical tasks. It takes a look at the underlying—and fascinating—math principles that power machine learning but also shows that you don't need to be a math whiz to build fun new tools and apply them to your work and study. Understand the history of AI and machine learning Work with Python 3.8 and TensorFlow 2.x (and R as a download) Build and test your own models Use the latest datasets, rather than the worn out data found in other books Apply machine learning to real problems Whether you want to learn for college or to enhance your business or career performance, this friendly beginner's guide is your best introduction to machine learning, allowing you to become quickly confident using this amazing and fast-developing technology that's impacting lives for the better all over the world.

Machine Learning and Its Application

Author : Indranath Chatterjee
Publisher :
ISBN 13 : 9781681089423
Total Pages : 356 pages
Book Rating : 4.0/5 (894 download)

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Book Synopsis Machine Learning and Its Application by : Indranath Chatterjee

Download or read book Machine Learning and Its Application written by Indranath Chatterjee and published by . This book was released on 2021-12-22 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and Its Application: A Quick Guide for Beginners aims to cover most of the core topics required for study in machine learning curricula included in university and college courses. The textbook introduces readers to central concepts in machine learning and artificial intelligence, which include the types of machine learning algorithms and the statistical knowledge required for devising relevant computer algorithms. The book also covers advanced topics such as deep learning and feature engineering. Key features: - 8 organized chapters on core concepts of machine learning for learners - Accessible text for beginners unfamiliar with complex mathematical concepts - Introductory topics are included, including supervised learning, unsupervised learning, reinforcement learning and predictive statistics - Advanced topics such as deep learning and feature engineering provide additional information - Introduces readers to python programming with examples of code for understanding and practice - Includes a summary of the text and a dedicated section for references Machine Learning and Its Application: A Quick Guide for Beginners is an essential book for students and learners who want to understand the basics of machine learning and equip themselves with the knowledge to write algorithms for intelligent data processing applications.

Machine Learning For Beginners Guide Algorithms

Author : William Sullivan
Publisher : PublishDrive
ISBN 13 : 9781975632328
Total Pages : 268 pages
Book Rating : 4.6/5 (323 download)

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Book Synopsis Machine Learning For Beginners Guide Algorithms by : William Sullivan

Download or read book Machine Learning For Beginners Guide Algorithms written by William Sullivan and published by PublishDrive. This book was released on 2017-08-19 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machines can LEARN ?!?! Machine learning occurs primarily through the use of " algorithms" and other elaborate procedures Whether you're a novice, intermediate or expert this book will teach you all the ins, outs and everything you need to know about machine learning Note: Bonus chapters included inside! Instead of spending hundreds or even thousands of dollars on courses/materials why not read this book instead? Its a worthwhile read and the most valuable investment you can make for yourself Other books easily retail for $50-$100+ and have far less quality content. This book is by far superior and exceeds any other book available for beginners. What You'll Learn Supervised Learning Unsupervised Learning Reinforced Learning Algorithms Decision Tree Random Forest Neural Networks Python Deep Learning And much, much more! This is the most comprehensive and easy to read step by step guide in machine learning that exists. Learn from one of the most reliable programmers alive and expert in the field You do not want to miss out on this incredible offer!

Beginner's Guide to Code Algorithms

Author : Deepankar Maitra
Publisher : CRC Press
ISBN 13 : 1000535770
Total Pages : 189 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Beginner's Guide to Code Algorithms by : Deepankar Maitra

Download or read book Beginner's Guide to Code Algorithms written by Deepankar Maitra and published by CRC Press. This book was released on 2022-01-26 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do you have creative ideas that you wish you could transform into code? Do you want to boost your problem solving and logic skills? Do you want to enhance your career by adopting an algorithmic mindset? In our increasingly digital world, coding is an essential skill. Communicating an algorithm to a machine to perform a set of tasks is vital. Beginner’s Guide to Code Algorithms: Experiments to Enhance Productivity and Solve Problems written by Deepankar Maitra teaches you how to think like a programmer. The author unravels the secret behind writing code – building a good algorithm. Algorithmic thinking leads to asking the right question and enables a shift from issue resolution to value creation. Having this mindset will make you more marketable to employers. This book takes you on a problem-solving journey to expand your mind and increase your willingness to experiment with code. You will: Learn the art of building an algorithm through hands-on exercises Understand how to develop code for inspiring productivity concepts Build a mentality of developing algorithms to solve problems Develop, test, review, and improve code through guided experimentation This book is designed to develop a culture of logical thinking through intellectual stimulation. It will benefit students and teachers of programming, business professionals, as well as experienced users of Microsoft Excel who wish to become proficient with macros.

Machine Learning with Python

Author : Oliver Theobald
Publisher : Packt Publishing Ltd
ISBN 13 : 1835462073
Total Pages : 146 pages
Book Rating : 4.8/5 (354 download)

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Book Synopsis Machine Learning with Python by : Oliver Theobald

Download or read book Machine Learning with Python written by Oliver Theobald and published by Packt Publishing Ltd. This book was released on 2024-03-06 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the secrets of data science and machine learning with our comprehensive Python course, designed to take you from basics to complex algorithms effortlessly Key Features Navigate through Python's machine learning libraries effectively Learn exploratory data analysis and data scrubbing techniques Design and evaluate machine learning models with precision Book DescriptionThe course starts by setting the foundation with an introduction to machine learning, Python, and essential libraries, ensuring you grasp the basics before diving deeper. It then progresses through exploratory data analysis, data scrubbing, and pre-model algorithms, equipping you with the skills to understand and prepare your data for modeling. The journey continues with detailed walkthroughs on creating, evaluating, and optimizing machine learning models, covering key algorithms such as linear and logistic regression, support vector machines, k-nearest neighbors, and tree-based methods. Each section is designed to build upon the previous, reinforcing learning and application of concepts. Wrapping up, the course introduces the next steps, including an introduction to Python for newcomers, ensuring a comprehensive understanding of machine learning applications.What you will learn Analyze datasets for insights Scrub data for model readiness Understand key ML algorithms Design and validate models Apply Linear and Logistic Regression Utilize K-Nearest Neighbors and SVMs Who this book is for This course is ideal for aspiring data scientists and professionals looking to integrate machine learning into their workflows. A basic understanding of Python and statistics is beneficial.

Machine Learning for Beginners

Author : Ethem Mining
Publisher :
ISBN 13 : 9781671268425
Total Pages : 222 pages
Book Rating : 4.2/5 (684 download)

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Book Synopsis Machine Learning for Beginners by : Ethem Mining

Download or read book Machine Learning for Beginners written by Ethem Mining and published by . This book was released on 2019-12-03 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you fascinated about machine learning and AI and you don't know where to start? Have you ever heard people talking about Machine Learning but you only have a vague idea of the actual meaning? Do you want to understand how machine learning could simplify your daily life? Imagine a world where computing systems understand people and the world around us them to a point where they can notice patterns, collect data, interpret it and give recommendations to solve real world problems with high level of precision. It sounds like science fiction but it is happening in healthcare, agriculture, cyber security, facial recognition, targeting and retargeting customers in online advertising, recommending specific products, stories, videos, text etc., self-driving cars, real time pricing, predicting human behavior and much more. Now imagine you being one of the people behind the code; the people who get these advanced systems to work the way they do. Would it be a dream come true for you? By virtue that you are reading this, it is clear that you have some special liking for this advanced tech and would want to learn how you can be one of the people behind the code. Even if not, you probably want to be able to understand the inner workings of these systems. The concept may sound extremely out there and advanced but it won't be if you follow this guide, which takes an easy to follow, beginner friendly language to help you to understand the ins and outs of machine learning! Here is a summary of what this book will teach you: The basics of machine learning, including what it is, how machine learning has evolved over the years, the application of machine learning in today's world and the future of machine learning How machine learning is beneficial in today's world The different approaches to machine learning, including unsupervised, supervised, reinforcement learning method, semi-supervised machine learning and many others The concept of big data analysis, including what is big data, why big data is important, the application of big data in today's world as well as the different data analysis tools that you can use The link between big data and machine learning The different machine learning algorithms, including what machine-learning algorithms are and how and when the different learning algorithms are used The concept of artificial neural networks, including how they work, when to use neural networks and more How decision trees are used in machine learning, including what decision trees are (in respect to machine learning), how they work, how the decision tree is read, the different nodes in decision trees and when to use them The ins and outs of linear and logistic regression in machine learning, including what linear regression is, different types of regression, how linear regression works, how linear regression is used and much more And much more! Even if this is your first encounter with the concept of machine learning, this book will uncover everything you need to know to master machine learning and possibly get started in this field of advanced computing knowing very well what you are venturing into. And the good thing is that the book takes a beginner friendly approach to help you to apply what you learn right away! Would You Like To Know More? Click Buy Now With 1-Click or Buy Now to get started!

Machine Learning for Beginners

Author : Jason Knox
Publisher :
ISBN 13 : 9781672473088
Total Pages : 147 pages
Book Rating : 4.4/5 (73 download)

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Book Synopsis Machine Learning for Beginners by : Jason Knox

Download or read book Machine Learning for Beginners written by Jason Knox and published by . This book was released on 2019-12-07 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thinking about beginning a career in the field of Data Science? Do you want to understand more in depth everything that concerns Machine Learning? Or maybe you're a total newbie eager to start learning this topic from zero or so. Machine Learning is one of the most exciting developments to come out of computer science since its founding. It's dramatically changing society all around us and the new occupation of Data Science which has arisen as a result of the development of Machine Learning has opened up a new career path that guarantees employment that is exciting, at the cutting edge, and guaranteed to be challenging. Maybe you're aware of all the hype but you are quite sure what Machine Learning is. If that's the case you've come to the right place. This book is designed to be a beginner's introduction to the exciting world of Machine Learning and Data Science. In this book we are going to pull the curtain back and reveal the secrets and tools used in these exciting fields. We'll begin by recounting a history of machines and how they are an extension of the human mind and also an extension of human labor. Then we will introduce you to the concept of Machine Learning and explore how it relates to Artificial Intelligence into Deep Learning. You will learn all the different ways that Machine Learning can be applied in the real world in practical circumstances. After this, we will reveal the different types of learning and training that is used in order to get computers to learn how to deal with the real world and become autonomous agents. We will teach you all about Supervised and Unsupervised Learning. You're also going to learn the concepts behind all the major algorithms that are used in Data Science and Machine Learning. Inside you'll discover: What Linear Regression is, and the concept of least squares; Types of learning used to train machines to think and act autonomously; Avoid getting lost in Decision Trees and Random Forests; Understand Logistic Regression; Learn how tools like Clustering are used; Find out some of the recent applications of Machine Learning to the real world; See how Machine Learning is being used in Social Media, Analysis, by Government and by companies like Amazon, Netflix and Google; And much more... So, don't waste anymore time and let's start your journey !! ***Scroll up and click the BUY NOW button***

Machine Learning for Beginners

Author : Steven Cooper
Publisher : Roland Bind
ISBN 13 :
Total Pages : 85 pages
Book Rating : 4.:/5 (661 download)

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Book Synopsis Machine Learning for Beginners by : Steven Cooper

Download or read book Machine Learning for Beginners written by Steven Cooper and published by Roland Bind. This book was released on 2018-09-07 with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you are looking for a complete beginners guide to learn machine learning with examples, in just a few hours, then you need to continue reading. Machine learning is an incredibly dense topic. It's hard to imagine condensing it into an easily readable and digestible format. However, this book aims to do exactly that. ★★ Grab your copy today and learn ★★ ♦ The different types of learning algorithm that you can expect to encounter ♦ The numerous applications of machine learning ♦ The different types of machine learning and how they differ ♦ The best practices for picking up machine learning ♦ What languages and libraries to work with ♦ The future of machine learning ♦ The various problems that you can solve with machine learning algorithms ♦ And much more... Starting from nothing, we slowly work our way through all the concepts that are central to machine learning. By the end of this book, you're going to feel as though you have an extremely firm understanding of what machine learning is, how it can be used, and most importantly, how it can change the world. You're also going to have an understanding of the logic behind the algorithms and what they aim to accomplish. Don't waste your time working with a book that's only going to make an already complicated topic even more complicated. Scroll up and click the buy now button to learn everything you need to know about Machine Learning!

Python Machine Learning

Author : Railey Brandon
Publisher : Roland Bind
ISBN 13 :
Total Pages : 152 pages
Book Rating : 4.:/5 (661 download)

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Book Synopsis Python Machine Learning by : Railey Brandon

Download or read book Python Machine Learning written by Railey Brandon and published by Roland Bind. This book was released on 2019-04-25 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: ★☆Have you come across the terms machine learning and neural networks in most articles you have recently read? Do you also want to learn how to build a machine learning model that will answer your questions within a blink of your eyes?☆★ If you responded yes to any of the above questions, you have come to the right place. Machine learning is an incredibly dense topic. It's hard to imagine condensing it into an easily readable and digestible format. However, this book aims to do exactly that. Machine learning and artificial intelligence have been used in different machines and applications to improve the user's experience. One can also use machine learning to make data analysis and predicting the output for some data sets easy. All you need to do is choose the right algorithm, train the model and test the model before you apply it on any real-world tool. It is that simple isn't it? ★★Apart from this, you will also learn more about★★ ♦ The Different Types Of Learning Algorithm That You Can Expect To Encounter ♦ The Numerous Applications Of Machine Learning And Deep Learning ♦ The Best Practices For Picking Up Neural Networks ♦ What Are The Best Languages And Libraries To Work With ♦ The Various Problems That You Can Solve With Machine Learning Algorithms ♦ And much more... Well, you can do it faster if you use Python. This language has made it easy for any user, even an amateur, to build a strong machine learning model since it has numerous directories and libraries that make it easy for one to build a model. Do you want to know how to build a machine learning model and a neural network? So, what are you waiting for? Grab a copy of this book now!

Hands-On Ensemble Learning with R

Author : Prabhanjan Narayanachar Tattar
Publisher : Packt Publishing Ltd
ISBN 13 : 1788629175
Total Pages : 376 pages
Book Rating : 4.7/5 (886 download)

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Book Synopsis Hands-On Ensemble Learning with R by : Prabhanjan Narayanachar Tattar

Download or read book Hands-On Ensemble Learning with R written by Prabhanjan Narayanachar Tattar and published by Packt Publishing Ltd. This book was released on 2018-07-27 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore powerful R packages to create predictive models using ensemble methods Key Features Implement machine learning algorithms to build ensemble-efficient models Explore powerful R packages to create predictive models using ensemble methods Learn to build ensemble models on large datasets using a practical approach Book Description Ensemble techniques are used for combining two or more similar or dissimilar machine learning algorithms to create a stronger model. Such a model delivers superior prediction power and can give your datasets a boost in accuracy. Hands-On Ensemble Learning with R begins with the important statistical resampling methods. You will then walk through the central trilogy of ensemble techniques – bagging, random forest, and boosting – then you'll learn how they can be used to provide greater accuracy on large datasets using popular R packages. You will learn how to combine model predictions using different machine learning algorithms to build ensemble models. In addition to this, you will explore how to improve the performance of your ensemble models. By the end of this book, you will have learned how machine learning algorithms can be combined to reduce common problems and build simple efficient ensemble models with the help of real-world examples. What you will learn Carry out an essential review of re-sampling methods, bootstrap, and jackknife Explore the key ensemble methods: bagging, random forests, and boosting Use multiple algorithms to make strong predictive models Enjoy a comprehensive treatment of boosting methods Supplement methods with statistical tests, such as ROC Walk through data structures in classification, regression, survival, and time series data Use the supplied R code to implement ensemble methods Learn stacking method to combine heterogeneous machine learning models Who this book is for This book is for you if you are a data scientist or machine learning developer who wants to implement machine learning techniques by building ensemble models with the power of R. You will learn how to combine different machine learning algorithms to perform efficient data processing. Basic knowledge of machine learning techniques and programming knowledge of R would be an added advantage.

A Human's Guide to Machine Intelligence

Author : Kartik Hosanagar
Publisher : Penguin
ISBN 13 : 0525560904
Total Pages : 274 pages
Book Rating : 4.5/5 (255 download)

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Book Synopsis A Human's Guide to Machine Intelligence by : Kartik Hosanagar

Download or read book A Human's Guide to Machine Intelligence written by Kartik Hosanagar and published by Penguin. This book was released on 2020-03-10 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Wharton professor and tech entrepreneur examines how algorithms and artificial intelligence are starting to run every aspect of our lives, and how we can shape the way they impact us Through the technology embedded in almost every major tech platform and every web-enabled device, algorithms and the artificial intelligence that underlies them make a staggering number of everyday decisions for us, from what products we buy, to where we decide to eat, to how we consume our news, to whom we date, and how we find a job. We've even delegated life-and-death decisions to algorithms--decisions once made by doctors, pilots, and judges. In his new book, Kartik Hosanagar surveys the brave new world of algorithmic decision-making and reveals the potentially dangerous biases they can give rise to as they increasingly run our lives. He makes the compelling case that we need to arm ourselves with a better, deeper, more nuanced understanding of the phenomenon of algorithmic thinking. And he gives us a route in, pointing out that algorithms often think a lot like their creators--that is, like you and me. Hosanagar draws on his experiences designing algorithms professionally--as well as on history, computer science, and psychology--to explore how algorithms work and why they occasionally go rogue, what drives our trust in them, and the many ramifications of algorithmic decision-making. He examines episodes like Microsoft's chatbot Tay, which was designed to converse on social media like a teenage girl, but instead turned sexist and racist; the fatal accidents of self-driving cars; and even our own common, and often frustrating, experiences on services like Netflix and Amazon. A Human's Guide to Machine Intelligence is an entertaining and provocative look at one of the most important developments of our time and a practical user's guide to this first wave of practical artificial intelligence.

Machine Learning

Author : Alexa Spencer
Publisher : Createspace Independent Publishing Platform
ISBN 13 : 9781983423789
Total Pages : 90 pages
Book Rating : 4.4/5 (237 download)

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Book Synopsis Machine Learning by : Alexa Spencer

Download or read book Machine Learning written by Alexa Spencer and published by Createspace Independent Publishing Platform. This book was released on 2017-12-30 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning Complete Beginners Guide For Neural Networks, Algorithms, Random Forests and Decision Trees Made Simple Most people encounter machine learning algorithms every day, though they likely don't stop to think about it. These are the programs that serve as the backbone of self-learning software. You'll find them at use in everything from Google's self-driving cars to Amazon's Alexa to the personalized recommendations on streaming services like Netflix. Here is a preview of what you'll learn: What machine learning is and how it's used in the real world The frameworks and languages used to write the algorithms An in-depth exploration of the most popular algorithms Advice for choosing and implementing an algorithm How to interpret the results and put them to use There are a lot of different ways that you can use these algorithms. They can help make your company more efficient, identify new customers and markets, or improve your ability to predict market trends. Knowledge is the first step to get you started, and this book is designed to get you up to speed. Download your copy of "Machine Learning" by scrolling up and clicking "Buy Now With 1-Click" button. Tags: Machine Learning, Machine Learning Algorithms, Algorithms, Neural Networks, Random Forests, Decision Trees Machine, Machine Learning Course, Big Data Machine Learning, Machine Learning For Dummies, Machine Learning Big Data, Machine Learning Tools, Machine Learning Basics, Machine Learning Online Course, Learn Machine Learning, Machine Learning As A Service, Cloud Machine Learning, Big Data And Machine Learning, Machine Learning And Big Data, Machine Learning Algorithms For Beginners, Machine Learning Platform, Data Science, Machine Learning Big Data Analytics, Machine Learning Companies, Ai Machine Learning, Machine Learning Cloud, Machine Learning Services

Machine Learning

Author : Ryan Turner
Publisher : Publishing Factory
ISBN 13 :
Total Pages : 94 pages
Book Rating : 4./5 ( download)

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Book Synopsis Machine Learning by : Ryan Turner

Download or read book Machine Learning written by Ryan Turner and published by Publishing Factory . This book was released on 2020-04-19 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you someone who is interested in how the next generation of machines can help you? Is Artificial Intelligence something to be feared, or do you imagine it that it will change our lives for the better? This book will provide the answers you need. Life is becoming ever more complex as we struggle to keep up with technology and use it to our best advantage. It is also more hectic and less certain, even in some of the mundane aspects of our lives, so that we are constantly trying to keep pace. New advancements in technology are paving the way to making life easier for billions and now things like Machine Learning and AI are changing the way we live. In this book, Machine Learning: The Ultimate Beginner’s Guide to Learn Machine Learning, Artificial Intelligence & Neural Networks Step by Step, you will see how this new technology continuously improves itself, can identify trends and patterns with ease and handles a wide variety of data, with chapters that explore: • Teaching the basic principles of Machine Learning • Why it is important and the many benefits that it provides • How Machine Learning differs from conventional programming • The fundamentals of algorithms • Challenges with Machine Learning and how you can easily overcome them • How it is going to change the future and make life easier • And much more… Machine Learning and AI are more than just science fiction. They are here now and undoubtedly will remain, improving and enhancing our lives in many ways, from the everyday to the vitally important. This book provides a platform that will give you a comprehensive understanding, that is second to none, of machine learning and its place in the world today. Get a copy now and see how Machine Learning will change your life!

Machine Learning For Dummies

Author : John Paul Mueller
Publisher : John Wiley & Sons
ISBN 13 : 1119245516
Total Pages : 432 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Machine Learning For Dummies by : John Paul Mueller

Download or read book Machine Learning For Dummies written by John Paul Mueller and published by John Wiley & Sons. This book was released on 2016-05-31 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Your no-nonsense guide to making sense of machine learning Machine learning can be a mind-boggling concept for the masses, but those who are in the trenches of computer programming know just how invaluable it is. Without machine learning, fraud detection, web search results, real-time ads on web pages, credit scoring, automation, and email spam filtering wouldn't be possible, and this is only showcasing just a few of its capabilities. Written by two data science experts, Machine Learning For Dummies offers a much-needed entry point for anyone looking to use machine learning to accomplish practical tasks. Covering the entry-level topics needed to get you familiar with the basic concepts of machine learning, this guide quickly helps you make sense of the programming languages and tools you need to turn machine learning-based tasks into a reality. Whether you're maddened by the math behind machine learning, apprehensive about AI, perplexed by preprocessing data—or anything in between—this guide makes it easier to understand and implement machine learning seamlessly. Grasp how day-to-day activities are powered by machine learning Learn to 'speak' certain languages, such as Python and R, to teach machines to perform pattern-oriented tasks and data analysis Learn to code in R using R Studio Find out how to code in Python using Anaconda Dive into this complete beginner's guide so you are armed with all you need to know about machine learning!

Deep Learning for Beginners

Author : Dr. Pablo Rivas
Publisher : Packt Publishing Ltd
ISBN 13 : 1838647589
Total Pages : 416 pages
Book Rating : 4.8/5 (386 download)

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Book Synopsis Deep Learning for Beginners by : Dr. Pablo Rivas

Download or read book Deep Learning for Beginners written by Dr. Pablo Rivas and published by Packt Publishing Ltd. This book was released on 2020-09-18 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Implement supervised, unsupervised, and generative deep learning (DL) models using Keras and Dopamine with TensorFlow Key FeaturesUnderstand the fundamental machine learning concepts useful in deep learningLearn the underlying mathematical concepts as you implement deep learning models from scratchExplore easy-to-understand examples and use cases that will help you build a solid foundation in DLBook Description With information on the web exponentially increasing, it has become more difficult than ever to navigate through everything to find reliable content that will help you get started with deep learning. This book is designed to help you if you're a beginner looking to work on deep learning and build deep learning models from scratch, and you already have the basic mathematical and programming knowledge required to get started. The book begins with a basic overview of machine learning, guiding you through setting up popular Python frameworks. You will also understand how to prepare data by cleaning and preprocessing it for deep learning, and gradually go on to explore neural networks. A dedicated section will give you insights into the working of neural networks by helping you get hands-on with training single and multiple layers of neurons. Later, you will cover popular neural network architectures such as CNNs, RNNs, AEs, VAEs, and GANs with the help of simple examples, and learn how to build models from scratch. At the end of each chapter, you will find a question and answer section to help you test what you've learned through the course of the book. By the end of this book, you'll be well-versed with deep learning concepts and have the knowledge you need to use specific algorithms with various tools for different tasks. What you will learnImplement recurrent neural networks (RNNs) and long short-term memory (LSTM) for image classification and natural language processing tasksExplore the role of convolutional neural networks (CNNs) in computer vision and signal processingDiscover the ethical implications of deep learning modelingUnderstand the mathematical terminology associated with deep learningCode a generative adversarial network (GAN) and a variational autoencoder (VAE) to generate images from a learned latent spaceImplement visualization techniques to compare AEs and VAEsWho this book is for This book is for aspiring data scientists and deep learning engineers who want to get started with the fundamentals of deep learning and neural networks. Although no prior knowledge of deep learning or machine learning is required, familiarity with linear algebra and Python programming is necessary to get started.

Machine Learning Made Easy: A Beginner's Guide for All

Author : M.B. Chatfield
Publisher : M.B. Chatfield
ISBN 13 :
Total Pages : 258 pages
Book Rating : 4./5 ( download)

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Book Synopsis Machine Learning Made Easy: A Beginner's Guide for All by : M.B. Chatfield

Download or read book Machine Learning Made Easy: A Beginner's Guide for All written by M.B. Chatfield and published by M.B. Chatfield. This book was released on with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unleash the power of machine learning to automate tasks, make predictions, and solve complex problems. Machine learning is a powerful tool that can be used to automate tasks, make predictions, and solve complex problems. It is used in a wide variety of industries, including healthcare, finance, and manufacturing. Machine Learning Made Easy is the perfect resource for anyone who wants to learn the basics of machine learning. This comprehensive guide covers everything you need to know, from the basics of machine learning algorithms to advanced topics such as deep learning. Whether you're a student, a business professional, or a data enthusiast, Machine Learning Made Easy is the essential resource for learning about machine learning. Here are some of the key topics covered in the book: Introduction to machine learning Types of machine learning algorithms Choosing the right machine learning algorithm Training a machine learning model Evaluating a machine learning model Using machine learning to automate tasks Using machine learning to make predictions If you are a beginner who wants to learn about machine learning, Machine Learning Made Easy is a great place to start.