Practical Deep Learning with PyTorch: PyTorch implementation for computer vision, NLP, audio, and language translation

Practical Deep Learning with PyTorch: PyTorch implementation for computer vision, NLP, audio, and language translation (English Edition)

Practical Deep Learning with PyTorch: PyTorch implementation for computer vision, NLP, audio, and language translation (English Edition)

Author:Deepak Gowda (Author)

Publisher finelybook 出版社:‏ BPB Publications

Publication Date 出版日期: 2025-04-08

Language 语言: English

Print Length 页数: 286 pages

ISBN-10: 9365897254

ISBN-13: 9789365897258

Book Description

Description

Deep learning is revolutionizing how we solve complex problems, and PyTorch has emerged as a leading framework for its ease of use and flexibility. This book is designed to bridge the gap between theory and practice, providing a hands-on approach to understanding deep learning with PyTorch. It covers fundamental and advanced topics, including object detection, NLP, GANs, and time series forecasting.

The book begins with foundational deep learning concepts and guides you through setting up PyTorch. You will learn to manipulate tensors, load data, build models, and understand computer vision with multi-object detection using YOLO to enhance image recognition through transfer learning techniques. You will also analyze generative models with GANs for data augmentation and venture into audio processing with text-to-speech and speech-to-text using TorchAudio. Learn NLP tasks like text classification, summarization, sentiment analysis, and question answering with pre-trained models like BERT. Finally, learn to tackle time series forecasting using RNNs, LSTMs, CNNs, and transformers.

By the end of this book, you will be equipped with the practical skills and knowledge to confidently build and deploy deep learning solutions across various domains, helping you innovate in the ever-evolving field of artificial intelligence.

What you will learn

● Implement deep learning models for image, text, and speech tasks.

● Build and optimize AI workflows using PyTorch efficiently.

● Apply transfer learning techniques for improved model performance.

● Develop GANs for generating high-quality synthetic data.

● Use NLP techniques for language processing and sentiment analysis.

● Forecast time series data using LSTMs and deep learning models.

Who this book is for

This book is for AI enthusiasts, data scientists, and engineers seeking practical knowledge of deep learning. Whether you are a beginner exploring AI or a seasoned professional optimizing deep learning architectures, this book provides essential techniques, tools, and best practices to help you excel in the field of artificial intelligence.

Table of Contents

1. A Primer on Deep Learning

2. Getting PyTorch Setup and Running

3. Multi-object Detection

4. Image Labeling Using Transfer Learning

5. Harnessing Generative Adversarial Network for Data Augmentation

6. Building Text-to-speech Models

7. Converting Speech-to-text Using TorchAudio

8. Text Analysis, Categorization, and Language Translation

9. Text Summarization and Sentiment Analysis

10. Time Series Forecasting Using Deep Learning

Amazon Page

下载地址

PDF, (conv), EPUB | 20 MB | 2025-07-03
下载地址 Download解决验证以访问链接!
打赏
未经允许不得转载:finelybook » Practical Deep Learning with PyTorch: PyTorch implementation for computer vision, NLP, audio, and language translation

评论 抢沙发

觉得文章有用就打赏一下

您的打赏,我们将继续给力更多优质内容

支付宝扫一扫

微信扫一扫