All Projects → rahul-raj → Java Deep Learning Cookbook

rahul-raj / Java Deep Learning Cookbook

Licence: mit
Code for Java Deep Learning Cookbook

Programming Languages

java
68154 projects - #9 most used programming language

Projects that are alternatives of or similar to Java Deep Learning Cookbook

100daysofmlcode
My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge.
Stars: ✭ 146 (-6.41%)
Mutual labels:  artificial-intelligence, classification, artificial-neural-networks, linear-regression, regression
Machine Learning From Scratch
Succinct Machine Learning algorithm implementations from scratch in Python, solving real-world problems (Notebooks and Book). Examples of Logistic Regression, Linear Regression, Decision Trees, K-means clustering, Sentiment Analysis, Recommender Systems, Neural Networks and Reinforcement Learning.
Stars: ✭ 42 (-73.08%)
Mutual labels:  artificial-intelligence, classification, reinforcement-learning, regression
Text summurization abstractive methods
Multiple implementations for abstractive text summurization , using google colab
Stars: ✭ 359 (+130.13%)
Mutual labels:  artificial-intelligence, reinforcement-learning, deeplearning, machinelearning
Tensorflow Book
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
Stars: ✭ 4,448 (+2751.28%)
Mutual labels:  classification, reinforcement-learning, linear-regression, regression
Free Ai Resources
🚀 FREE AI Resources - 🎓 Courses, 👷 Jobs, 📝 Blogs, 🔬 AI Research, and many more - for everyone!
Stars: ✭ 192 (+23.08%)
Mutual labels:  artificial-intelligence, reinforcement-learning, machinelearning, artificial-neural-networks
Mariana
The Cutest Deep Learning Framework which is also a wonderful Declarative Language
Stars: ✭ 151 (-3.21%)
Mutual labels:  artificial-intelligence, deeplearning, machinelearning, artificial-neural-networks
Coursera Natural Language Processing Specialization
Programming assignments from all courses in the Coursera Natural Language Processing Specialization offered by deeplearning.ai.
Stars: ✭ 39 (-75%)
Mutual labels:  artificial-intelligence, deeplearning, nlp-machine-learning
Php Ml
PHP-ML - Machine Learning library for PHP
Stars: ✭ 7,900 (+4964.1%)
Mutual labels:  artificial-intelligence, classification, regression
Brihaspati
Collection of various implementations and Codes in Machine Learning, Deep Learning and Computer Vision ✨💥
Stars: ✭ 53 (-66.03%)
Mutual labels:  artificial-intelligence, artificial-neural-networks, linear-regression
Pycm
Multi-class confusion matrix library in Python
Stars: ✭ 1,076 (+589.74%)
Mutual labels:  artificial-intelligence, classification, deeplearning
Sru Deeplearning Workshop
دوره 12 ساعته یادگیری عمیق با چارچوب Keras
Stars: ✭ 66 (-57.69%)
Mutual labels:  classification, deeplearning, regression
Mlkit
A simple machine learning framework written in Swift 🤖
Stars: ✭ 144 (-7.69%)
Mutual labels:  artificial-intelligence, linear-regression, regression
Yannl
Yet another neural network library
Stars: ✭ 37 (-76.28%)
Mutual labels:  classification, artificial-neural-networks, regression
Artificialintelligenceengines
Computer code collated for use with Artificial Intelligence Engines book by JV Stone
Stars: ✭ 35 (-77.56%)
Mutual labels:  artificial-intelligence, reinforcement-learning, deeplearning
The Deep Learning With Keras Workshop
An Interactive Approach to Understanding Deep Learning with Keras
Stars: ✭ 34 (-78.21%)
Mutual labels:  classification, artificial-neural-networks, regression
Letslearnai.github.io
Lets Learn AI
Stars: ✭ 33 (-78.85%)
Mutual labels:  artificial-intelligence, machinelearning, nlp-machine-learning
Machine Learning With Python
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
Stars: ✭ 2,197 (+1308.33%)
Mutual labels:  artificial-intelligence, classification, regression
Ml
A high-level machine learning and deep learning library for the PHP language.
Stars: ✭ 1,270 (+714.1%)
Mutual labels:  artificial-intelligence, classification, regression
Malware Classification
Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine for Malware Classification
Stars: ✭ 88 (-43.59%)
Mutual labels:  artificial-intelligence, classification, artificial-neural-networks
Tensorflow cookbook
Code for Tensorflow Machine Learning Cookbook
Stars: ✭ 5,984 (+3735.9%)
Mutual labels:  classification, linear-regression, regression

Java deep learning cookbook

Java Deep Learning Cookbook

This is a code repository for the upcoming book "Java Deep Learning cookbook" sponsored by Packt Publishing. We use and promote deeplearning4j library for all use-cases in this book. Official deeplearning4j version targeted in this cookbook is 1.0.0-beta3. For the same reason, some of the methods or approaches discussed in this cookbook may get deprecated in their newer versions. So, be sure to refer their latest API documentation. You may use newer versions that has bug fixes and new features.

Update

Java deep learning cookbook is released on November 8, 2019.

Build

Each chapter will have separate source folder where all examples are stored for the particular chapter. For example, if you want to import the code for chapter 2, navigate to the chapter directory first and then import the directory sourceCode/cookbook-app in your IDE. You should also see pom.xml located there.

cookbookworkspace

From Intellij IDE

  • Navigate to the sourceCode root directory.
  • Open as a Maven project and compile.

From Command Line

mvn clean install

If you face issues with Intellij being not able to detect dependencies or any workspace issues, try running the below command:

mvn idea:idea

Delete workspace.xml under .idea directory if problem persists.

Table of Contents

  1. Introduction to Deep Learning in Java
  2. Data Extraction, Transform and Loading
  3. Building Deep Neural Networks for Binary classification
  4. Building Convolutional Neural Networks
  5. Implementing NLP
  6. Constructing LTSM Network for time series
  7. Constructing LTSM Neural network for sequence classification
  8. Performing Anomaly detection on unsupervised data
  9. Using RL4J for Reinforcement learning
  10. Developing applications in distributed environment
  11. Applying Transfer Learning to network models
  12. Benchmarking and Neural Network Optimization
Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].