Implement Neural Network Solutions With Scikit Learn And Pytorch
4.2 out of 5
Language | : | English |
File size | : | 16017 KB |
Text-to-Speech | : | Enabled |
Enhanced typesetting | : | Enabled |
Print length | : | 437 pages |
Screen Reader | : | Supported |
What you'll learn
- The fundamentals of neural networks
- How to use Scikit-Learn to build and train neural network models
- How to use PyTorch to build and train neural network models
- How to deploy neural network models to production
Who this book is for
This book is for anyone who wants to learn how to implement neural network solutions. Whether you're a beginner or an experienced programmer, this book will teach you everything you need to know to get started.
About the author
I am a data scientist with over 10 years of experience in machine learning and deep learning. I have worked on a variety of projects, including developing neural network models for image classification, natural language processing, and time series forecasting. I am passionate about teaching and helping others learn about neural networks.
Table of contents
- to neural networks
- Building and training neural network models with Scikit-Learn
- Building and training neural network models with PyTorch
- Deploying neural network models to production
Reviews
"This book is a great to neural networks. It is well-written and easy to follow, and it provides a comprehensive overview of the topic." - *****
"I highly recommend this book to anyone who wants to learn about neural networks. It is a great resource for both beginners and experienced programmers." - *****
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4.2 out of 5
Language | : | English |
File size | : | 16017 KB |
Text-to-Speech | : | Enabled |
Enhanced typesetting | : | Enabled |
Print length | : | 437 pages |
Screen Reader | : | Supported |
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4.2 out of 5
Language | : | English |
File size | : | 16017 KB |
Text-to-Speech | : | Enabled |
Enhanced typesetting | : | Enabled |
Print length | : | 437 pages |
Screen Reader | : | Supported |