Book

Machine Learning with PyTorch and Scikit-Learn

Fully updated with PyTorch and the latest additions to scikit-learn. Packed with clear explanations, visualizations, and working examples, the book covers essential machine learning techniques in depth, along with two cutting-edge machine learning techniques: transformers and graph neural networks.

Offered byPackt Logo

Difficulty Level

Intermediate

Completion Time

25h48m

Language

English

About Book

Who Is This Book For?

If you have a good grasp of Python basics and want to start learning about machine learning and deep learning, then this is the book for you. This is an essential resource written for developers and data scientists who want to create practical machine learning and deep learning applications using scikit-learn and PyTorch. Before you get started with this book, you’ll need a good understanding of calculus, as well as linear algebra.

Book content

chapters 25h48m total length

Giving Computers the Ability to Learn from Data

Training Simple Machine Learning Algorithms for Classification

A Tour of Machine Learning Classifiers Using Scikit-Learn

Building Good Training Datasets – Data Preprocessing

Compressing Data via Dimensionality Reduction

Learning Best Practices for Model Evaluation and Hyperparameter Tuning

Combining Different Models for Ensemble Learning

Applying Machine Learning to Sentiment Analysis

Predicting Continuous Target Variables with Regression Analysis

Working with Unlabeled Data – Clustering Analysis

Implementing a Multilayer Artificial Neural Network from Scratch

Parallelizing Neural Network Training with PyTorch

Going Deeper – The Mechanics of PyTorch

Classifying Images with Deep Convolutional Neural Networks

Modeling Sequential Data Using Recurrent Neural Networks

Transformers – Improving Natural Language Processing with Attention Mechanisms

Generative Adversarial Networks for Synthesizing New Data

Graph Neural Networks for Capturing Dependencies in Graph Structured Data

Reinforcement Learning for Decision Making in Complex Environments

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