Summary Of Oliver Theobalds Machine Learning For Absolute Beginners

Author : Milkyway Media
Publisher : Milkyway Media
ISBN 13 :
Total Pages : 16 pages
Book Rating : 4./5 ( download)

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Download or read book Summary of Oliver Theobald's Machine Learning for Absolute Beginners written by Milkyway Media and published by Milkyway Media. This book was released on 2024-03-26 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get the Summary of Oliver Theobald's Machine Learning for Absolute Beginners in 20 minutes. Please note: This is a summary & not the original book. "Machine Learning for Absolute Beginners" by Oliver Theobald provides an introduction to the expansive field of data science, which includes big data, AI, data mining, and machine learning. The book traces the evolution of data analysis from classical statistics, which could be managed manually, to the complex, computer-dependent techniques of today. It explains how AI aims to replicate human cognitive abilities and how machine learning, a subset of AI, uses algorithms to learn from data and make predictions...

Author : Oliver Theobald
Publisher : Packt Publishing Ltd
ISBN 13 : 1835462073
Total Pages : 146 pages
Book Rating : 4.72/5 ( download)

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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.

Author : Oliver Theobald
Publisher :
ISBN 13 : 9781081762469
Total Pages : 88 pages
Book Rating : 4.62/5 ( download)

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Download or read book Data Analytics for Absolute Beginners: a Deconstructed Guide to Data Literacy written by Oliver Theobald and published by . This book was released on 2019-07-21 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: While exposure to data has become more or less a daily ritual for the rank-and-file knowledge worker, true understanding-treated in this book as data literacy-resides in knowing what lies behind the data. Everything from the data's source to the specific choice of input variables, algorithmic transformations, and visual representation shape the accuracy, relevance, and value of the data and mark its journey from raw data to business insight. It's also important to grasp the terminology and basic concepts of data analytics as much as it is to have the financial literacy to be successful as a decisionmaker in the business world. In this book, we make sense of data analytics without the assumption that you understand specific data science terminology or advanced programming languages to set you on your path. Topics covered in this book: Data Mining Big Data Machine Learning Alternative Data Data Management Web Scraping Regression Analysis Clustering Analysis Association Analysis Data Visualization Business Intelligence

Author : John Paul Mueller
Publisher : John Wiley & Sons
ISBN 13 : 1119724015
Total Pages : 471 pages
Book Rating : 4.18/5 ( download)

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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.

Author : Hui Jiang
Publisher : Cambridge University Press
ISBN 13 : 1108837042
Total Pages : 423 pages
Book Rating : 4.40/5 ( download)

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Download or read book Machine Learning Fundamentals written by Hui Jiang and published by Cambridge University Press. This book was released on 2021-11-25 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: A coherent introduction to core concepts and deep learning techniques that are critical to academic research and real-world applications.

Author : Oliver Theobald
Publisher :
ISBN 13 :
Total Pages : 180 pages
Book Rating : 4.26/5 ( download)

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Download or read book Machine Learning for Absolute Beginners written by Oliver Theobald and published by . This book was released on 2021 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Featured by Tableau as the first of "7 Books About Machine Learning for Beginners." Ready to spin up a virtual GPU instance and smash through petabytes of data? Want to add 'Machine Learning' to your LinkedIn profile?Well, hold on there...Before you embark on your journey, there are some high-level theory and statistical principles to weave through first. But rather than spend $30-$50 USD on a thick textbook, you may want to read this book first. As a clear and concise alternative, this book provides a high-level introduction to machine learning, free downloadable code exercises, and video demonstrations. Machine Learning for Absolute Beginners Third Edition has been written and designed for absolute beginners. This means plain-English explanations and no coding experience required. Where core algorithms are introduced, clear explanations and visual examples are added to make it easy to follow along at home.This new edition also features extended chapters with quizzes, free supplementary online video tutorials for coding models in Python, and downloadable resources not included in the Second Edition. Readers of the Second Edition should not feel compelled to purchase this Third Edition.Disclaimer: If you have passed the 'beginner' stage in your study of machine learning and are ready to tackle coding and deep learning, you would be well served with a long-format textbook. If, however, you are yet to reach that Lion King moment - as a fully grown Simba looking over the Pride Lands of Africa - then this is the book to gently hoist you up and give a clear lay of the land.In this step-by-step guide you will learn: - How to download free datasets- What tools and machine learning libraries you need- Data scrubbing techniques, including one-hot encoding, binning and dealing with missing data- Preparing data for analysis, including k-fold Validation- Regression analysis to create trend lines- k-Means Clustering to find new relationships- The basics of Neural Networks- Bias/Variance to improve your machine learning model- Decision Trees to decode classification, and- How to build your first Machine Learning Model to predict house values using PythonFrequently Asked QuestionsQ: Do I need programming experience to complete this e-book?A: This e-book is designed for absolute beginners, so no programming experience is required. However, two of the later chapters introduce Python to demonstrate an actual machine learning model, so you will see some programming used in this book. Q: I have already purchased the Second Edition of Machine Learning for Absolute Beginners, should I purchase this Third Edition?A: As the same topics from the Second Edition are covered in the Third Edition, you may be better served reading a more advanced title on machine learning. If you have purchased a previous edition of this book and wish to get access to the free video tutorials, please email the author. Q: Does this book include everything I need to become a machine learning expert?A: Unfortunately, no. This book is designed for readers taking their first steps in machine learning and further learning will be required beyond this book to master machine learning.

Author : Oliver Theobald
Publisher : Machine Learning for Beginners
ISBN 13 : 9781726769037
Total Pages : 120 pages
Book Rating : 4.38/5 ( download)

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Download or read book Machine Learning: Make Your Own Recommender System written by Oliver Theobald and published by Machine Learning for Beginners. This book was released on 2018-10-06 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn How to Make Your Own Recommender System in an Afternoon.Recommender systems are one of the most visible applications of machine learning and data mining today and their uncanny ability to convert our unspoken actions into items we desire is both addicting and concerning. And whether recommender systems excite or scare you, the best way to manage their influence and impact is to understand the architecture and algorithms that play on your personal data. Recommender systems are here to stay and for anyone beginning their journey in data science, this is a lucrative space for future employment.This book will get you up and running with the basics as well as the steps to coding your own recommender system. Exercises include predicting book recommendations, relevant house properties for online marketing purposes, and whether a user will click on an ad campaign. The contents of this book is designed for beginners with some background knowledge of data science, including classical statistics and computing programming. If this is your first exposure to data science, you may want to spend a few hours to read my first book Machine Learning for Absolute Beginners before you get started here.Topics covered in this book: Setting Up A Sandbox Environment With Jupyter NotebookWorking With DataData ReductionBuilding a Collaborative Filtering ModelBuilding a Content-Based Filtering ModelEvaluationPrivacy & EthicsFuture of Recommender SystemsPlease feel welcome to join this introductory course by buying a copy or sending a free sample to your preferred device.

Author : Chris Sebastian
Publisher : Python, Machine Learning
ISBN 13 : 9781793016423
Total Pages : 164 pages
Book Rating : 4.29/5 ( download)

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Download or read book Machine Learning for Beginners written by Chris Sebastian and published by Python, Machine Learning. This book was released on 2019 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: ♦♦Bonus: Buy the Paperback version of this book, and get the kindle eBook version included for FREE** Machine Learning is changing the world. You use Machine Learning every day and probably don't know it. In this book, you will learn how ML grew from a desire to make computers able to learn. Trace the development of Machine Learning from the early days of a computer learning how to play checkers, to machines able to beat world masters in chess and go. Understand how large data is so important to Machine Learning, and how the collection of massive amounts of data provides Machine Learning programmers with the information they need to developing learning algorithms.Simple examples will help you understand the complex math and probability statistics underlining Machine Learning. You will also see real-world examples of Machine Learning in action and uncover how these algorithms are making your life better every day.Learn about how artificial intelligence, Machine Learning, Neural Networks, and Swarm Intelligence interact and complement each other as part of the quest to generate machines capable of thinking and reacting to the world. Read about the technical issues with Machine Learning and how they are being overcome. Discover the dark side of ML and what possible outcomes there could be should things go wrong. And finally, learn about the positive future artificial intelligence and Machine Learning promise to bring to the world. In this book, you will discover *The history of Machine Learning *Approaches taken to ML in the past and present *Artificial intelligence and its relationship to ML *How neural networks, big data, regression, and the cloud all play a part in the development of Machine Learning *Compare Machine Learning to the Internet of Things, Robotics, and Swarm Intelligence *Learn about the different models of ML and how each is used to produce learning algorithms *Get access to free software and data sets so you can try out your very own Machine Learning software *Examine some of the technical problems and philosophical dilemmas with ML *See what advanced Machine Learning will make to our world in the future So what are you waiting for???Scroll back up and order this book NOW.

Author : Andriy Burkov
Publisher :
ISBN 13 : 9781999579500
Total Pages : 141 pages
Book Rating : 4.0X/5 ( download)

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Download or read book The Hundred-page Machine Learning Book written by Andriy Burkov and published by . This book was released on 2019 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a practical guide to get started and execute on machine learning within a few days without necessarily knowing much about machine learning.The first five chapters are enough to get you started and the next few chapters provide you a good feel of more advanced topics to pursue.

Author : Chris Albon
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491989335
Total Pages : 305 pages
Book Rating : 4.33/5 ( download)

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Download or read book Machine Learning with Python Cookbook written by Chris Albon and published by "O'Reilly Media, Inc.". This book was released on 2018-03-09 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or numerical data, model selection, and dimensionality reduction and many other topics. Each recipe includes code that you can copy and paste into a toy dataset to ensure that it actually works. From there, you can insert, combine, or adapt the code to help construct your application. Recipes also include a discussion that explains the solution and provides meaningful context. This cookbook takes you beyond theory and concepts by providing the nuts and bolts you need to construct working machine learning applications. You’ll find recipes for: Vectors, matrices, and arrays Handling numerical and categorical data, text, images, and dates and times Dimensionality reduction using feature extraction or feature selection Model evaluation and selection Linear and logical regression, trees and forests, and k-nearest neighbors Support vector machines (SVM), naïve Bayes, clustering, and neural networks Saving and loading trained models