Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

The Supervised Learning Workshop

You're reading from The Supervised Learning Workshop Predict outcomes from data by building your own powerful predictive models with machine learning in Python

Product type Paperback

Published in Feb 2020

Publisher Packt

ISBN-13 9781800209046

Length 532 pages

Edition 2nd Edition

Languages

Python

Tools

Jupyter

Concepts

Machine Learning

Authors (4):

Blaine Bateman

Ashish Ranjan Jha

Ishita Mathur

Benjamin Johnston

View More author details

Table of Contents (9) Chapters

Preface

1. Fundamentals

2. Exploratory Data Analysis and Visualization FREE CHAPTER

3. Linear Regression

4. Autoregression

5. Classification Techniques

6. Ensemble Modeling

7. Model Evaluation

Appendix

1. Fundamentals

Overview

This chapter introduces you to supervised learning, using Anaconda to manage coding environments, and using Jupyter notebooks to create, manage, and run code. It also covers some of the most common Python packages used in supervised learning: pandas, NumPy, Matplotlib, and seaborn. By the end of this chapter, you will be able to install and load Python libraries into your development environment for use in analysis and machine learning problems. You will also be able to load an external data source using pandas, and use a variety of methods to search, filter, and compute descriptive statistics of the data. This chapter will enable you to gauge the potential impact of various issues such as missing data, class imbalance, and low sample size within the data source.

The rest of the chapter is locked

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.

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 $19.99/month. Cancel anytime

Authors (4)

Blaine Bateman

Blaine Bateman

Blaine Bateman has more than 35 years of experience working with various industries from government R&D to startups to $1B public companies. His experience focuses on analytics including machine learning and forecasting. His hands-on abilities include Python and R coding, Keras/Tensorflow, and AWS & Azure machine learning services. As a machine learning consultant, he has developed and deployed actual ML models in industry.

See other products by Blaine Bateman

Mathur

Mathur

Ishita Mathur has worked as a data scientist for 2.5 years with product-based start-ups working with business concerns in various domains and formulating them as technical problems that can be solved using data and machine learning. Her current work at GO-JEK involves the end-to-end development of machine learning projects, by working as part of a product team on defining, prototyping, and implementing data science models within the product. She completed her masters' degree in high-performance computing with data science at the University of Edinburgh, UK, and her bachelor's degree with honors in physics at St. Stephen's College, Delhi.

See other products by Mathur

Ashish Ranjan Jha

Ashish Ranjan Jha

Ashish Ranjan Jha received his bachelor's degree in electrical engineering from IIT Roorkee (India), a master's degree in Computer Science from EPFL (Switzerland), and an MBA degree from Quantic School of Business (Washington). He has received a distinction in all 3 of his degrees. He has worked for large technology companies, including Oracle and Sony as well as the more recent tech unicorns such as Revolut, mostly focused on artificial intelligence. He currently works as a machine learning engineer. Ashish has worked on a range of products and projects, from developing an app that uses sensor data to predict the mode of transport to detecting fraud in car damage insurance claims. Besides being an author, machine learning engineer, and data scientist, he also blogs frequently on his personal blog site about the latest research and engineering topics around machine learning.

See other products by Ashish Ranjan Jha

Benjamin Johnston

Benjamin Johnston

Benjamin Johnston is a senior data scientist for one of the world's leading data-driven MedTech companies and is involved in the development of innovative digital solutions throughout the entire product development pathway, from problem definition to solution research and development, through to final deployment. He is currently completing his Ph.D. in machine learning, specializing in image processing and deep convolutional neural networks. He has more than 10 years of experience in medical device design and development, working in a variety of technical roles, and holds first-class honors bachelor's degrees in both engineering and medical science from the University of Sydney, Australia.

See other products by Benjamin Johnston

Other recommended products

Related to this chapter

Data Preprocessing with Python for Absolute Beginners

Data Preprocessing with Python for Absolute Beginners

This book is dedicated to data preparation and explains how to perform different data preparation techniques on various datasets using different data preparation libraries written in the Python programming language. Whether you are new to programming or beginning your journey toward data science and machine learning, a solid foundation in data preparation is a must.

Mar 2021 8h 16m

Python Feature Engineering Cookbook

Python Feature Engineering Cookbook

Feature engineering is invaluable for developing and enriching your machine learning models. In this book, you will work with the best Python tools to streamline your feature engineering pipelines, feature engineering techniques and simplify and improve the quality of your code.

Jan 2020 12h 24m

Python Feature Engineering Cookbook

Python Feature Engineering Cookbook

Feature engineering is invaluable for developing and enriching your machine learning models. In this book, you will work with the best Python tools to streamline your feature engineering pipelines, feature engineering techniques and simplify and improve the quality of your code.

Jan 2020 12h 24m

Python Feature Engineering Cookbook

Python Feature Engineering Cookbook

Feature engineering is invaluable for developing and enriching your machine learning models. In this book, you will work with the best Python tools to streamline your feature engineering pipelines, feature engineering techniques and simplify and improve the quality of your code.

Jan 2020 12h 24m

Python Feature Engineering Cookbook

Python Feature Engineering Cookbook

Feature engineering is invaluable for developing and enriching your machine learning models. In this book, you will work with the best Python tools to streamline your feature engineering pipelines, feature engineering techniques and simplify and improve the quality of your code.

Jan 2020 12h 24m

Python Feature Engineering Cookbook

Python Feature Engineering Cookbook

Feature engineering is invaluable for developing and enriching your machine learning models. In this book, you will work with the best Python tools to streamline your feature engineering pipelines, feature engineering techniques and simplify and improve the quality of your code.

Jan 2020 12h 24m

Python Feature Engineering Cookbook

Python Feature Engineering Cookbook

Feature engineering is invaluable for developing and enriching your machine learning models. In this book, you will work with the best Python tools to streamline your feature engineering pipelines, feature engineering techniques and simplify and improve the quality of your code.

Jan 2020 12h 24m

Python Feature Engineering Cookbook

Python Feature Engineering Cookbook

Feature engineering is invaluable for developing and enriching your machine learning models. In this book, you will work with the best Python tools to streamline your feature engineering pipelines, feature engineering techniques and simplify and improve the quality of your code.

Jan 2020 12h 24m

Python Feature Engineering Cookbook

Python Feature Engineering Cookbook

Feature engineering is invaluable for developing and enriching your machine learning models. In this book, you will work with the best Python tools to streamline your feature engineering pipelines, feature engineering techniques and simplify and improve the quality of your code.

Jan 2020 12h 24m

Python Feature Engineering Cookbook

Python Feature Engineering Cookbook

Feature engineering is invaluable for developing and enriching your machine learning models. In this book, you will work with the best Python tools to streamline your feature engineering pipelines, feature engineering techniques and simplify and improve the quality of your code.

Jan 2020 12h 24m

The Data Analysis Workshop

The Data Analysis Workshop

The Data Analysis Workshop is a comprehensive guide that shows you how to analyze your data and gain insights into your business. Starting with the basics of data analysis, including data visualization and exploratory data analysis, this book takes you through the complete spectrum of techniques, such as time series analysis and categorical data analysis. It is the ideal companion on your journey to becoming an expert data analyst.

Jul 2020 20h 52m

The Data Analysis Workshop

The Data Analysis Workshop

The Data Analysis Workshop is a comprehensive guide that shows you how to analyze your data and gain insights into your business. Starting with the basics of data analysis, including data visualization and exploratory data analysis, this book takes you through the complete spectrum of techniques, such as time series analysis and categorical data analysis. It is the ideal companion on your journey to becoming an expert data analyst.

Jul 2020 20h 52m

Personalised recommendations for you

Based on your interests and search pattern

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m