Neural Networks Without Python
Build an Image Captioning System with Java Neural NetworksBy Paloma Iqbal
Length7h 29m
About this audiobook
deep learning Java and neural networks Java. Java deep learning without Python? Yes. Neural networks in Java from scratch. Build, train, and tune models with pure JVM code. This hands-on guide walks you through every layer—from perceptrons to CNNs—using worked examples you can run today. No Python, no wrappers, just Java. Paloma Iqbal, a veteran JVM engineer, shows you how to implement backpropagation, optimize hyperparameters, and deploy models in production. Whether you're a beginner or pro, you'll master deep learning for Java developers with clear, actionable code. 2084 and the AI Revolution, Updated and Expanded Edition by Wallace Henley and AI for Beginners by David A. Heisenthal offer broader AI perspectives, but this book is your practical toolkit for JVM-based neural networks. Start coding now.
This hands-on AI/ML/Data guide is written to be used at the keyboard: every concept is paired with something you can run, adapt, and keep. You move from first principles to real, working results, with the common errors and fixes called out along the way so you are never stuck for long.
This hands-on AI/ML/Data guide is written to be used at the keyboard: every concept is paired with something you can run, adapt, and keep. You move from first principles to real, working results, with the common errors and fixes called out along the way so you are never stuck for long.
This hands-on AI/ML/Data guide is written to be used at the keyboard: every concept is paired with something you can run, adapt, and keep. You move from first principles to real, working results, with the common errors and fixes called out along the way so you are never stuck for long.
Audiobook details
GenreTechnology
Length7 hrs 29 mins
Narrated byListen with 1,000+ voices
FormateBook with Audio
LanguageEnglish
Table of contents
1Neural Networks Without Python
2Preface
3Chapter 1 — Setting Up the Image Captioning Project
4Chapter 2 — Neural Network Fundamentals in Java
5Chapter 3 — Backpropagation and Optimization
Show all chaptersShow less
6Chapter 4 — Deep Neural Networks: From Shallow to Deep
7Chapter 5 — Convolutional Neural Networks: The Image Encoder
8Chapter 6 — Feature Extraction with Pre-Trained CNNs
9Chapter 7 — Recurrent Neural Networks: The Text Decoder
10Chapter 8 — Long Short-Term Memory Networks
11Chapter 9 — Gated Recurrent Units and Alternatives
12Chapter 10 — Sequence-to-Sequence Models and Attention Mechanism
13Chapter 11 — Advanced Optimizers and Regularization
14Chapter 12 — Data Augmentation and Preprocessing for Captions
15Chapter 13 — Evaluating Image Captioning Models
16Chapter 14 — Hyperparameter Tuning and Experiment Tracking
17Chapter 15 — Deploying the Captioning Model as a REST API
18Chapter 16 — Performance Optimization and GPU Acceleration
19Chapter 17 — Ethical Considerations and Future Directions
20About the Author
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