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Author: Matt Harrison
Publisher: "O'Reilly Media, Inc."
ISBN: 149204749X
Category : Computers
Languages : en
Pages : 230
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Book Description
With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project. Ideal for programmers, data scientists, and AI engineers, this book includes an overview of the machine learning process and walks you through classification with structured data. You’ll also learn methods for clustering, predicting a continuous value (regression), and reducing dimensionality, among other topics. This pocket reference includes sections that cover: Classification, using the Titanic dataset Cleaning data and dealing with missing data Exploratory data analysis Common preprocessing steps using sample data Selecting features useful to the model Model selection Metrics and classification evaluation Regression examples using k-nearest neighbor, decision trees, boosting, and more Metrics for regression evaluation Clustering Dimensionality reduction Scikit-learn pipelines
Author: Matt Harrison
Publisher: "O'Reilly Media, Inc."
ISBN: 149204749X
Category : Computers
Languages : en
Pages : 230
Get Book Here
Book Description
With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project. Ideal for programmers, data scientists, and AI engineers, this book includes an overview of the machine learning process and walks you through classification with structured data. You’ll also learn methods for clustering, predicting a continuous value (regression), and reducing dimensionality, among other topics. This pocket reference includes sections that cover: Classification, using the Titanic dataset Cleaning data and dealing with missing data Exploratory data analysis Common preprocessing steps using sample data Selecting features useful to the model Model selection Metrics and classification evaluation Regression examples using k-nearest neighbor, decision trees, boosting, and more Metrics for regression evaluation Clustering Dimensionality reduction Scikit-learn pipelines
Author: Matt Harrison
Publisher: O'Reilly Media
ISBN: 1492047511
Category : Computers
Languages : en
Pages : 321
Get Book Here
Book Description
With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project. Ideal for programmers, data scientists, and AI engineers, this book includes an overview of the machine learning process and walks you through classification with structured data. You’ll also learn methods for clustering, predicting a continuous value (regression), and reducing dimensionality, among other topics. This pocket reference includes sections that cover: Classification, using the Titanic dataset Cleaning data and dealing with missing data Exploratory data analysis Common preprocessing steps using sample data Selecting features useful to the model Model selection Metrics and classification evaluation Regression examples using k-nearest neighbor, decision trees, boosting, and more Metrics for regression evaluation Clustering Dimensionality reduction Scikit-learn pipelines
Author: James Densmore
Publisher: O'Reilly Media
ISBN: 1492087807
Category : Computers
Languages : en
Pages : 277
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Book Description
Data pipelines are the foundation for success in data analytics. Moving data from numerous diverse sources and transforming it to provide context is the difference between having data and actually gaining value from it. This pocket reference defines data pipelines and explains how they work in today's modern data stack. You'll learn common considerations and key decision points when implementing pipelines, such as batch versus streaming data ingestion and build versus buy. This book addresses the most common decisions made by data professionals and discusses foundational concepts that apply to open source frameworks, commercial products, and homegrown solutions. You'll learn: What a data pipeline is and how it works How data is moved and processed on modern data infrastructure, including cloud platforms Common tools and products used by data engineers to build pipelines How pipelines support analytics and reporting needs Considerations for pipeline maintenance, testing, and alerting
Author: Mohamed Sabri
Publisher: BPB Publications
ISBN: 9390684978
Category : Computers
Languages : en
Pages : 437
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Book Description
Discover one of the most complete dictionaries in data science. KEY FEATURES ● Simplified understanding of complex concepts, terms, terminologies, and techniques. ● Combined glossary of machine learning, mathematics, and statistics. ● Chronologically arranged A-Z keywords with brief description. DESCRIPTION This pocket guide is a must for all data professionals in their day-to-day work processes. This book brings a comprehensive pack of glossaries of machine learning, deep learning, mathematics, and statistics. The extensive list of glossaries comprises concepts, processes, algorithms, data structures, techniques, and many more. Each of these terms is explained in the simplest words possible. This pocket guide will help you to stay up to date of the most essential terms and references used in the process of data analysis and machine learning. WHAT YOU WILL LEARN ● Get absolute clarity on every concept, process, and algorithm used in the process of data science operations. ● Keep yourself technically strong and sound-minded during data science meetings. ● Strengthen your knowledge in the field of Big data and business intelligence. WHO THIS BOOK IS FOR This book is for data professionals, data scientists, students, or those who are new to the field who wish to stay on top of industry jargon and terminologies used in the field of data science. TABLE OF CONTENTS 1. Chapter one: A 2. Chapter two: B 3. Chapter three: C 4. Chapter four: D 5. Chapter five: E 6. Chapter six: F 7. Chapter seven: G 8. Chapter eight: H 9. Chapter nine: I 10. Chapter ten: J 11. Chapter 11: K 12. Chapter 12: L 13. Chapter 13: M 14. Chapter 14: N 15. Chapter 15: O 16. Chapter 16: P 17. Chapter 17: Q 18. Chapter 18: R 19. Chapter 19 : S 20. Chapter 20 : T 21. Chapter 21 : U 22. Chapter 22 : V 23. Chapter 23: W 24. Chapter 24: X 25. Chapter 25: Y 26. Chapter 26 : Z
Author: Mark Lutz
Publisher: "O'Reilly Media, Inc."
ISBN: 144935694X
Category : Computers
Languages : en
Pages : 215
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Book Description
Updated for both Python 3.4 and 2.7, this convenient pocket guide is the perfect on-the-job quick reference. Youâ??ll find concise, need-to-know information on Python types and statements, special method names, built-in functions and exceptions, commonly used standard library modules, and other prominent Python tools. The handy index lets you pinpoint exactly what you need. Written by Mark Lutzâ??widely recognized as the worldâ??s leading Python trainerâ??Python Pocket Reference is an ideal companion to Oâ??Reillyâ??s classic Python tutorials, Learning Python and Programming Python, also written by Mark. This fifth edition covers: Built-in object types, including numbers, lists, dictionaries, and more Statements and syntax for creating and processing objects Functions and modules for structuring and reusing code Pythonâ??s object-oriented programming tools Built-in functions, exceptions, and attributes Special operator overloading methods Widely used standard library modules and extensions Command-line options and development tools Python idioms and hints The Python SQL Database API
Author: Michael Fitzgerald
Publisher: "O'Reilly Media, Inc."
ISBN: 1491925973
Category : Computers
Languages : en
Pages : 179
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Book Description
Updated for Ruby 2.2, this handy reference offers brief yet clear explanations of Ruby’s core elements—from operators to blocks to documentation creation—and highlights the key features you may work with every day. Need to know the correct syntax for a conditional? Forgot the name of that String method? This book is organized to help you find the facts fast. Ruby Pocket Reference, 2nd Edition is ideal for experienced programmers who are new to Ruby. Whether you’ve come to Ruby because of Rails, or you want to take advantage of this clean, powerful, and expressive language for other applications, this reference will help you easily pinpoint the information you need. You’ll find detailed reference material for: Keywords, operators, comments, numbers, and symbols Variables, pre-defined global variables, and regular expressions Conditional statements, method use, classes, and exception handling Methods for the BasicObject, Object, Kernel, String, Array, and Hash classes Time formatting directives New syntax since Ruby 1.9
Author: Tony Stubblebine
Publisher: "O'Reilly Media, Inc."
ISBN: 0596514271
Category : Computers
Languages : en
Pages : 129
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Book Description
A guide to the syntax and semantics of regular expressions for Perl 5.8, Ruby, Java, PHP, C#, .NET, Python, JavaScript, and PCRE.
Author: Joe Papa
Publisher: "O'Reilly Media, Inc."
ISBN: 1492089974
Category : Computers
Languages : en
Pages : 310
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Book Description
This concise, easy-to-use reference puts one of the most popular frameworks for deep learning research and development at your fingertips. Author Joe Papa provides instant access to syntax, design patterns, and code examples to accelerate your development and reduce the time you spend searching for answers. Research scientists, machine learning engineers, and software developers will find clear, structured PyTorch code that covers every step of neural network development-from loading data to customizing training loops to model optimization and GPU/TPU acceleration. Quickly learn how to deploy your code to production using AWS, Google Cloud, or Azure and deploy your ML models to mobile and edge devices. Learn basic PyTorch syntax and design patterns Create custom models and data transforms Train and deploy models using a GPU and TPU Train and test a deep learning classifier Accelerate training using optimization and distributed training Access useful PyTorch libraries and the PyTorch ecosystem
Author: Oswald Campesato
Publisher: Mercury Learning and Information
ISBN: 168392469X
Category : Computers
Languages : en
Pages : 268
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Book Description
As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to basic machine learning concepts and incorporate that knowledge into Angular applications. The book is intended to be a fast-paced introduction to some basic features of machine learning and an overview of several popular machine learning classifiers. It includes code samples and numerous figures and covers topics such as Angular functionality, basic machine learning concepts, classification algorithms, TensorFlow and Keras. The files with code and color figures are on the companion disc with the book or available from the publisher. Features: Introduces the basic machine learning concepts and Angular applications Includes source code and full color figures
Author: Peter Prinz
Publisher: O'Reilly Media
ISBN: 0596528566
Category : Computers
Languages : en
Pages : 142
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Book Description
C is one of the oldest programming languages and still one of the most widely used. Whether you're an experienced C programmer or you're new to the language, you know how frustrating it can be to hunt through hundreds of pages in your reference books to find that bit of information on a certain function, type or other syntax element. Or even worse, you may not have your books with you. Your answer is the C Pocket Reference. Concise and easy to use, this handy pocket guide to C is a must-have quick reference for any C programmer. It's the only C reference that fits in your pocket and is an excellent companion to O'Reilly's other C books.Ideal as an introduction for beginners and a quick reference for advanced programmers, the C Pocket Reference consists of two parts: a compact description of the C language and a thematically structured reference to the standard library. The representation of the language is based on the ANSI standard and includes extensions introduced in 1999. An index is included to help you quickly find the information you need.This small book covers the following: C language fundamentals Data types Expressions and operators C statements Declarations Functions Preprocessor directives The standard library O'Reilly's Pocket References have become a favorite among programmers everywhere. By providing a wealth of important details in a concise, well-organized format, these handy books deliver just what you need to complete the task at hand. When you've reached a sticking point in your work and need to get to a solution quickly, the new C Pocket Reference is the book you'll want to have.
