0

Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Python Machine Learning Blueprints

You're reading from Python Machine Learning Blueprints Put your machine learning concepts to the test by developing real-world smart projects

Product type Paperback

Published in Jan 2019

Publisher Packt

ISBN-13 9781788994170

Length 378 pages

Edition 2nd Edition

Languages

Python

Tools

GitHub

Concepts

Machine Learning

Authors (3):

Michael Roman

Alexander Combs

Saurabh Chhajed

View More author details

Table of Contents (13) Chapters

Preface

1. The Python Machine Learning Ecosystem FREE CHAPTER

2. Build an App to Find Underpriced Apartments

3. Build an App to Find Cheap Airfares

4. Forecast the IPO Market Using Logistic Regression

5. Create a Custom Newsfeed

6. Predict whether Your Content Will Go Viral

7. Use Machine Learning to Forecast the Stock Market

8. Classifying Images with Convolutional Neural Networks

9. Building a Chatbot

10. Build a Recommendation Engine

11. What's Next?

12. Other Books You May Enjoy

Leave a review - let other readers know what you think

What's Next?

So far, we've used machine learning (ML) to implement various tasks. There are many advancements in the field of ML, and with each passing day, the areas in which it is applied are increasing too.

In this chapter, we'll summarize the projects that we executed in the previous chapters.

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 €18.99/month. Cancel anytime

Authors (3)

Chhajed

Chhajed

Saurabh Chhajed is a technologist with vast professional experience in building Enterprise applications that span across product and service industries. He has experience building some of the largest recommender engines using big data analytics and machine learning, and also enjoys acting as an evangelist for big data and NoSQL technologies. With his rich technical experience, Saurabh has helped some of the largest financial and industrial companies in USA build their large product suites and distributed applications from scratch. He shares his personal experiences with technology at http://saurzcode.in. Saurabh has also reviewed books by Packt Publishing, Apache Camel Essentials and Java EE 7 Development with NetBeans 8, in the past.

See other products by Chhajed

Combs

Combs

Alexander Combs is an experienced data scientist, strategist, and developer with a background in financial data extraction, natural language processing and generation, and quantitative and statistical modeling. He currently lives and works in New York City.

See other products by Combs

Roman

Roman

Michael Roman is a data scientist at The Atlantic, where he designs, tests, analyzes, and productionizes machine learning models to address a range of business topics. Prior to this he was an associate instructor at a full-time data science immersive program in New York City. His interests include computer vision, propensity modeling, natural language processing, and entrepreneurship.

See other products by Roman

Other recommended products

Related to this chapter

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 8h 28m

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 8h 28m

Deep Learning for Natural Language Processing

Deep Learning for Natural Language Processing

Starting with the basics, this book teaches you how to choose from the various text pre-processing techniques and select the best model from the several neural network architectures for NLP issues.

Jun 2019 12h 24m

Deep Learning for Natural Language Processing

Deep Learning for Natural Language Processing

Starting with the basics, this book teaches you how to choose from the various text pre-processing techniques and select the best model from the several neural network architectures for NLP issues.

Jun 2019 12h 24m

Deep Learning Quick Reference

Deep Learning Quick Reference

This book is a practical guide to applying deep neural networks including MLPs, CNNs, LSTMs, and more in Keras and TensorFlow. Packed with useful hacks to solve real-world challenges along with the supported math and theory around each topic, this book will be a quick reference for training and optimize your deep neural networks.

Deep Learning Quick Reference

Deep Learning Quick Reference

This book is a practical guide to applying deep neural networks including MLPs, CNNs, LSTMs, and more in Keras and TensorFlow. Packed with useful hacks to solve real-world challenges along with the supported math and theory around each topic, this book will be a quick reference for training and optimize your deep neural networks.

Deep Learning Quick Reference

Deep Learning Quick Reference

This book is a practical guide to applying deep neural networks including MLPs, CNNs, LSTMs, and more in Keras and TensorFlow. Packed with useful hacks to solve real-world challenges along with the supported math and theory around each topic, this book will be a quick reference for training and optimize your deep neural networks.

Deep Learning Quick Reference

Deep Learning Quick Reference

This book is a practical guide to applying deep neural networks including MLPs, CNNs, LSTMs, and more in Keras and TensorFlow. Packed with useful hacks to solve real-world challenges along with the supported math and theory around each topic, this book will be a quick reference for training and optimize your deep neural networks.

Deep Learning Quick Reference

Deep Learning Quick Reference

This book is a practical guide to applying deep neural networks including MLPs, CNNs, LSTMs, and more in Keras and TensorFlow. Packed with useful hacks to solve real-world challenges along with the supported math and theory around each topic, this book will be a quick reference for training and optimize your deep neural networks.

Deep Learning Quick Reference

Deep Learning Quick Reference

This book is a practical guide to applying deep neural networks including MLPs, CNNs, LSTMs, and more in Keras and TensorFlow. Packed with useful hacks to solve real-world challenges along with the supported math and theory around each topic, this book will be a quick reference for training and optimize your deep neural networks.

Hands-On Python Natural Language Processing

Hands-On Python Natural Language Processing

This book provides a blend of both the theoretical and practical aspects of Natural Language Processing (NLP). It covers the concepts essential to develop a thorough understanding of NLP and also delves into a detailed discussion on NLP based use-cases such as language translation, sentiment analysis, etc. Every module covers real-world examples

Jun 2020 10h 32m

Hands-On Python Natural Language Processing

Hands-On Python Natural Language Processing

This book provides a blend of both the theoretical and practical aspects of Natural Language Processing (NLP). It covers the concepts essential to develop a thorough understanding of NLP and also delves into a detailed discussion on NLP based use-cases such as language translation, sentiment analysis, etc. Every module covers real-world examples

Jun 2020 10h 32m

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