Search icon Close icon
Search icon
Subscription
0
Cart icon
Close icon
You have no products in your basket yet
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Python Machine Learning - Third Edition

You're reading from  Python Machine Learning - Third Edition

Product type Book
Published in Dec 2019
Publisher Packt
ISBN-13 9781789955750
Pages 772 pages
Edition 3rd Edition
Languages
Concepts
Authors (2):
Sebastian Raschka Sebastian Raschka
Profile icon Sebastian Raschka
LinkedIn
Sebastian Raschka is an Assistant Professor of Statistics at the University of Wisconsin-Madison focusing on machine learning and deep learning research. As Lead AI Educator at Grid AI, Sebastian plans to continue following his passion for helping people get into machine learning and artificial intelligence.
See other products by Sebastian Raschka
Vahid Mirjalili Vahid Mirjalili
Profile icon Vahid Mirjalili
LinkedIn
Vahid Mirjalili is a deep learning researcher focusing on CV applications. Vahid received a Ph.D. degree in both Mechanical Engineering and Computer Science from Michigan State University.
See other products by Vahid Mirjalili
View More author details

Table of Contents (21) Chapters

Preface 1. Giving Computers the Ability to Learn from Data 2. Training Simple Machine Learning Algorithms for Classification 3. A Tour of Machine Learning Classifiers Using scikit-learn 4. Building Good Training Datasets – Data Preprocessing 5. Compressing Data via Dimensionality Reduction 6. Learning Best Practices for Model Evaluation and Hyperparameter Tuning 7. Combining Different Models for Ensemble Learning 8. Applying Machine Learning to Sentiment Analysis 9. Embedding a Machine Learning Model into a Web Application 10. Predicting Continuous Target Variables with Regression Analysis 11. Working with Unlabeled Data – Clustering Analysis 12. Implementing a Multilayer Artificial Neural Network from Scratch 13. Parallelizing Neural Network Training with TensorFlow 14. Going Deeper – The Mechanics of TensorFlow 15. Classifying Images with Deep Convolutional Neural Networks 16. Modeling Sequential Data Using Recurrent Neural Networks 17. Generative Adversarial Networks for Synthesizing New Data 18. Reinforcement Learning for Decision Making in Complex Environments 19. Other Books You May Enjoy 20. Index

Applying Machine Learning to Sentiment Analysis

In the modern internet and social media age, people's opinions, reviews, and recommendations have become a valuable resource for political science and businesses. Thanks to modern technologies, we are now able to collect and analyze such data most efficiently. In this chapter, we will delve into a subfield of natural language processing (NLP) called sentiment analysis and learn how to use machine learning algorithms to classify documents based on their polarity: the attitude of the writer. In particular, we are going to work with a dataset of 50,000 movie reviews from the Internet Movie Database (IMDb) and build a predictor that can distinguish between positive and negative reviews.

The topics that we will cover in the following sections include the following:

  • Cleaning and preparing text data
  • Building feature vectors from text documents
  • Training a machine learning model to classify positive and negative...
lock icon The rest of the chapter is locked
arrow left Previous Chapter
Chapter 1 of 21
Next Chapter arrow right
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Sign up now
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}

Authors (2)

Left arrow icon
Profile icon Sebastian Raschka
LinkedIn
Sebastian Raschka is an Assistant Professor of Statistics at the University of Wisconsin-Madison focusing on machine learning and deep learning research. As Lead AI Educator at Grid AI, Sebastian plans to continue following his passion for helping people get into machine learning and artificial intelligence.
See other products by Sebastian Raschka
Profile icon Vahid Mirjalili
LinkedIn
Vahid Mirjalili is a deep learning researcher focusing on CV applications. Vahid received a Ph.D. degree in both Mechanical Engineering and Computer Science from Michigan State University.
See other products by Vahid Mirjalili
Right arrow icon

Other recommended products

Related to this chapter
Left arrow icon
Mastering Machine Learning with scikit-learn
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.
Jul 2017 8 hours 28 minutes
Mastering Predictive Analytics with scikit-learn and TensorFlow
Mastering Predictive Analytics with scikit-learn and TensorFlow
In this book, you will find a range of methods to improve the performance of almost any predictive model, from ensemble methods to dimensionality reduction and cross-validation. You will learn the tools to produce advanced predictive models. In addition, you will dive into the exiting field of Deep Learning using TensorFlow.
Sep 2018 5 hours 8 minutes
Supervised Machine Learning with Python
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.
May 2019 5 hours 24 minutes
Python Data Mining Quick Start Guide
Python Data Mining Quick Start Guide
This book is an introduction to data mining and its practical demonstration of working with real-world data sets. With this book, you will be able to extract useful insights using common Python libraries. You will also learn key stages like data loading, cleaning, analysis, visualization to build an efficient data mining pipeline.
Apr 2019 6 hours 16 minutes
Machine Learning with scikit-learn Quick Start Guide
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.
Oct 2018 5 hours 44 minutes
Hands-On Deep Learning Algorithms with Python
Hands-On Deep Learning Algorithms with Python
This book introduces basic-to-advanced deep learning algorithms used in a production environment by AI researchers and principal data scientists; it explains algorithms intuitively, including the underlying math, and shows how to implement them using popular Python-based deep learning libraries such as TensorFlow.
Jul 2019 17 hours 4 minutes
R Deep Learning Cookbook
R Deep Learning Cookbook
Deep Learning is the next big thing. It is a part of machine learning. Its favorable results in application with huge and complex data is remarkable. This book will help you to get through the problems that you face during the execution of different tasks and understand hacks in deep learning, neural networks, and advanced machine learning techniques
Aug 2017 9 hours 36 minutes
Machine Learning for OpenCV
Machine Learning for OpenCV
Machine learning for OpenCV begins by introducing you to the essential concepts of statistical learning, such as classification and regression. Once all the basics are covered, you will start exploring various algorithms such as decision trees, support vector machines, and Bayesian networks, and learn how to combine them with other OpenCV functionality. As the book progresses, so will your machine learning skills, until you are ready to take on today's hottest topic in the field: Deep Learning. Combined with your having learned to select the right tool for the task, this book will make sure you get comfortable with all relevant machine learning fundamentals.
Jul 2017 12 hours 44 minutes
Hands-On Neural Networks with TensorFlow 2.0
Hands-On Neural Networks with TensorFlow 2.0
This book is a guide to the TensorFlow (TF) framework, from the static graph architecture of TF 1.x to the eager execution and all the new features introduced in TF 2.0. Neural Networks applications are developed throughout the book with the aim of making the reader capable of developing neural networks-based solutions to real problems using TF 2.0
Sep 2019 11 hours 56 minutes
Hands-On Generative Adversarial Networks with Keras
Hands-On Generative Adversarial Networks with Keras
This book will explore deep learning and generative models, and their applications in artificial intelligence. You will learn to evaluate and improve your GAN models by eliminating challenges that are encountered in real-world applications. You will implement GAN architectures in various domains such as computer vision, NLP, and audio processing
May 2019 9 hours 4 minutes
Deep Learning with PyTorch Quick Start Guide
Deep Learning with PyTorch Quick Start Guide
PyTorch is extremely powerful and yet easy to learn. It provides advanced features such as supporting multiprocessor, distributed and parallel computation. This book is an excellent entry point for those wanting to explore deep learning with PyTorch to harness its power.
Dec 2018 5 hours 16 minutes
Feature Engineering Made Easy
Feature Engineering Made Easy
Feature engineering is the most important step in creating powerful machine learning systems. This book will take you through the entire feature-engineering journey to make your machine learning much more systematic and effective.
Jan 2018 10 hours 32 minutes
Right arrow icon

Personalised recommendations for you

Based on your interests and search pattern
Left arrow icon
Et al.
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.
Aug 2023 7 hours 40 minutes
Generative AI with LangChain
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.
Dec 2023 12 hours 0 minutes
Generative AI with LangChain
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.
Dec 2023 12 hours 0 minutes
Generative AI with LangChain
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.
Dec 2023 12 hours 0 minutes
Generative AI with LangChain
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.
Dec 2023 12 hours 0 minutes
Mastering Tableau 2023
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.
Aug 2023 22 hours 48 minutes
Building AI Applications with ChatGPT APIs
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.
Sep 2023 8 hours 36 minutes
Building AI Applications with ChatGPT APIs
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.
Sep 2023 8 hours 36 minutes
Data Engineering with AWS
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.
Oct 2023 21 hours 12 minutes
Modern Data Architecture on AWS
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.
Aug 2023 14 hours 0 minutes
Practical Guide to Applied Conformal Prediction in Python
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.
Dec 2023 8 hours 0 minutes
TinyML Cookbook
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.
Nov 2023 22 hours 8 minutes
Right arrow icon