Packt+ | Advance your knowledge in tech

You're reading from Statistics for Machine Learning

Product typeBook

Published inJul 2017

Reading LevelIntermediate

PublisherPackt

ISBN-139781788295758

Edition1st Edition

Languages

Python

Concepts

Statistics

Author (1)

Pratap Dangeti

www.PacktPub.com

For support files and downloads related to your book, please visit www.PacktPub.com.

Did you know that Packt offers eBook versions of every book published, with PDF and ePub files available? You can upgrade to the eBook version at www.PacktPub.comand as a print book customer, you are entitled to a discount on the eBook copy. Get in touch with us at service@packtpub.com for more details.

At www.PacktPub.com, you can also read a collection of free technical articles, sign up for a range of free newsletters and receive exclusive discounts and offers on Packt books and eBooks.

https://www.packtpub.com/mapt

Get the most in-demand software skills with Mapt. Mapt gives you full access to all Packt books and video courses, as well as industry-leading tools to help you plan your personal development and advance your career.

Why subscribe?

Fully searchable across every book published by Packt
Copy and paste, print, and bookmark content
On demand and accessible via a web browser

The rest of the chapter is locked

You have been reading a chapter from

Statistics for Machine Learning

Published in: Jul 2017Publisher: PacktISBN-13: 9781788295758

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

undefined

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at $15.99/month. Cancel anytime

Author (1)

Pratap Dangeti

Pratap Dangeti develops machine learning and deep learning solutions for structured, image, and text data at TCS, analytics and insights, innovation lab in Bangalore. He has acquired a lot of experience in both analytics and data science. He received his master's degree from IIT Bombay in its industrial engineering and operations research program. He is an artificial intelligence enthusiast. When not working, he likes to read about next-gen technologies and innovative methodologies.
Read more about Pratap Dangeti

Other recommended products

Related to this chapter

Machine Learning with scikit-learn Quick Start Guide

Scikit-learn is a robust machine learning library for the Python programming language. It provides a set of supervised and unsupervised learning algorithms. This book is the easiest way to learn how to deploy, optimize and evaluate all the important machine learning algorithms that scikit-learn provides.

BookOct 2018172 pages

Mastering Machine Learning with scikit-learn

This book examines machine learning models including k-nearest neighbors, logistic regression, naive Bayes, random forests, and support vector machines. You will work through document classification, image recognition, and other example problems.

BookJul 2017254 pages

Hands-On Reinforcement Learning with Python

Reinforcement learning is a self-evolving type of machine learning that takes us closer to achieving true artificial intelligence. This easy-to-follow guide explains everything from scratch using rich examples written in Python.

BookJun 2018318 pages

Practical Reinforcement Learning

Reinforcement learning (RL) is becoming a popular tool for constructing autonomous systems that improve themselves with experience. We will break the RL framework into its core building blocks, and provide you with details of each element. This book is divided into three parts. The first part defines Reinforcement Learning and describes the basics and the Python and Java frameworks, which we are going to use later in the book. The second part discusses learning techniques with basic algorithms such as Temporal Difference, Monte Carlo, and Policy Gradient—all with practical examples. Lastly, in the third part we apply Reinforcement Learning with the most recent and widely used algorithms, via practical applications.

BookOct 2017336 pages

Supervised Machine Learning with Python

A supervised learning task infers a function from flagged training data and maps an input to an output based on sample input-output pairs. In this book, you will learn various machine learning techniques (such as linear and logistic regression) and gain the practical knowledge you need to quickly and powerfully apply algorithms to new problems.

BookMay 2019162 pages

Ensemble Machine Learning Cookbook

This book uses a recipe-based approach to showcase the power of machine learning algorithms to build ensemble models using Python libraries. Through this book, you will be able to pick up the code, understand in depth how it works, execute and implement it efficiently. This will be a desk reference to implement a wide range of tasks and solve the common and uncommon problems in ensemble machine learning domain.

BookJan 2019336 pages

Hands-On Ensemble Learning with Python

Ensemble learning can provide the necessary methods to improve the accuracy and performance of existing models. In this book, you'll understand how to combine different machine learning algorithms to produce more accurate results from your models.

BookJul 2019298 pages

Hands-On Reinforcement Learning with R

Reinforcement Learning is an exciting part of machine learning. It has uses in technology from autonomous cars to game playing, and creates algorithms that can adapt to environmental changes. This book helps to understand how to implement RL with R, and explores interesting practical examples, such as using tabular Q-learning to control robots.

BookDec 2019362 pages

Applied Supervised Learning with Python

Applied Supervised Learning with Python provides you a rich understanding of machine learning, one of the most pursued topics in information science, and Python, one of the most popular scripting languages. Through this book, you'll learn Jupyter Notebooks, the technology used in academic and commercial circles with in-line code running support.

BookApr 2019404 pages

Machine Learning with R

Brett Lantz teaches you how to uncover key insights and make new predictions with this hands-on, practical guide to machine learning with R. This third edition is for experienced R users and beginners. The book is fully updated to R 3.6, featuring newer and better libraries, advice on ethical and bias issues, and an introduction to deep learning.

BookApr 2019458 pages

scikit-learn Cookbook

scikit-learn has evolved as a robust library for machine learning applications in python with support for a wide range of supervised and unsupervised learning algorithms. This edition brings to you the various enhancements to its model implementations, API and bug fixes in the latest major release of scikit-learn to support Python. This book covers easy to follow recipes right from mathematical operations to implementing various supervised, unsupervised and deep learning algorithms with scikit-learn. Get practical hands-on knowledge to implement various models and algorithms like Multi-Layer Perceptrons, time-series split, MAE criterion for regression, criteria for gradient boosting, Classifier, Regressor, and much more.

BookNov 2017374 pages

The Supervised Learning Workshop

Taking an engaging and practical approach, The Supervised Learning Workshop teaches you how to predict the output of new data, based on the relationship and behavior of?existing datasets. You’ll learn at your own pace and use Python libraries and Jupyter to build intelligent predictive models.?

BookFeb 2020532 pages

Personalised recommendations for you

Based on your interests and search pattern

Et al.

Ever wonder why speech recognition systems don't understand the Scottish accent, or what would happen if an astronaut only ate mac 'n' cheese, or other spurious reflections you'd have at a bar? We did, then collated those deliberations into absurd research articles with fake figures and methodologies inspired by even more fictionally absurd studies.

BookAug 2023230 pages5

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

BookDec 2023360 pages4

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

BookDec 2023360 pages5

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

BookDec 2023360 pages1

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

BookDec 2023360 pages5

Mastering Tableau 2023

This book is a comprehensive resource to mastering your Tableau skills and becoming a BI expert. As you progress, you will learn how to build advanced dashboards and improve your storytelling to derive key business insight, as well as make you well-versed with advanced functionalities of Tableau in the business intelligence domain.

BookAug 2023684 pages

Building AI Applications with ChatGPT APIs

This guide covers all ChatGPT API features for effortless creation of robust AI powered apps. With its help, you’ll be able to leverage ChatGPT’s cutting-edge NLP models to take your app development skills to the next level. You’ll also work on ten exciting projects that will give you the practical know-how that you can apply to your existing applications.

BookSep 2023258 pages5

Building AI Applications with ChatGPT APIs

This guide covers all ChatGPT API features for effortless creation of robust AI powered apps. With its help, you’ll be able to leverage ChatGPT’s cutting-edge NLP models to take your app development skills to the next level. You’ll also work on ten exciting projects that will give you the practical know-how that you can apply to your existing applications.

BookSep 2023258 pages2

Data Engineering with AWS

Embark on a journey to master data engineering pipelines on AWS! Our book offers a hands-on experience of AWS services for ingesting, transforming, and consuming data. Whether you're an absolute beginner or someone with basic data engineering experience, this guide is an indispensable resource.

BookOct 2023636 pages5

Modern Data Architecture on AWS

Every organization wants an agile, performant, and cost-effective data platform that meets all their current and future business needs. Purpose-built AWS analytics services and their features play a big part in building such a modern data platform. This book brings to you all the design and architectural patterns that’ll help you achieve this goal.

BookAug 2023420 pages5

Practical Guide to Applied Conformal Prediction in Python

Discover the power of Conformal Prediction with the "Practical Guide to Applied Conformal Prediction in Python." Master the latest techniques to quantify uncertainty in machine learning and computer vision models, and seamlessly apply them to your industry applications.

BookDec 2023240 pages

TinyML Cookbook

With over 70 project-based recipes, the TinyML Cookbook is a practical guide that will help you to get the most out of your microcontrollers. It provides a comprehensive understanding of the theoretical foundations while giving you hands-on experience training ML models for deployment on Arduino Nano 33 BLE Sense, Raspberry Pi Pico, and SparkFun RedBoard Artemis Nano microcontrollers.

BookNov 2023664 pages