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NLP Java: 
Tribuo: 
MLPMNist using DL4J: 
- #business-general-semi-technical
- #classifier-decision-trees
- #correlated-cross-occurrence
- #genetic-algorithms
- #java-projects-related-technologies
- #natural-language-processing-nlp
- #neural-networks
- #recommendation-systems-collaborative-filtering-cf
- #data-science
- #machine-learning
- #deep-learning
- #reinforcement-learning
- #deep-learning
- #tools-libraries-other-resources
- #java-specification-requests
- #how-to-deploy-devops-serverless
- #misc
- #clojure
- #scala
- #visualisation
- #contributing
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- Extract business value from DS (Tweet)
- Why Java and the JVM Will Dominate the Future of Machine Learning, AI, and Big Data (Tweet)
- Machine Learning Made More Accessible During Businesses’ Learning Curve (Tweet)
- Why You Need AI for Security (Tweet)
- The Difference between AI, Machine Learning and Deep Learning (Tweet)
- The Brain as Computer: Bad at Math, Good at Everything Else - (Tweet)
- 4 Insights On Artificial Intelligence And The Future Of Work (Tweet)
- AI apps demand DevOps infrastructure automation (Tweet)
- Difference between Machine Learning, Data Science, AI, Deep Learning, and Statistics (Tweet)
- You Could Become an AI Master Before You Know It. Here’s How. (Tweet)
- Why Java Will Dominate the Future of Machine Learning, AI, and Big Data (Tweet) | About DeepNetts | Download DeepNetts
- A Java-based Evolutionary Computation Research System: ECJ 27
- Using Java for Artificial Intelligence [deadlink] (Tweet)
- Want A Bigger Bang From AI? Embed It Into Your Apps (Tweet)
- A Beginner's Guide to Automated Machine Learning & AI (Tweet)
- Five TED Talks on AI to watch (Tweet)
- ThinkGradient - Transcending human intelligence through research and development in AI
- Two years in the life of AI, ML, DL and Java
- Oracle AI blog posts
- Java AI libraries with Gluon Mobile
- Email Spam Detector java Application with ApacheSpark (Tweet)
- Guide to Artificial Intelligence: Automating Decision-Making (Tweet)
- Jenetics is an advanced Genetic Algorithm, respectively an Evolutionary Algorithm, library written in java (Tweet)
- JGAP is a Genetic Algorithms and Genetic Programming package written in Java
- JaGa - Genetic Algorithms in Java on a Powerful Generic Pluggable Architecture
- Project Panama and fast MachineLearning computation (Tweet)
- GraalVM + Machine Learning (Tweet)
- Deploying Bespoke AI using fnproj - KADlytics by Miminal (Tweet)
- Introduction to Neural Network Architectures (Tweet)
- Neural Networks explained by MIT (Tweet)
- Implementing an Artificial Neural Network in Pure Java (No external dependencies) (Tweet)
- How to build a simple neural network with Eclipse Deeplearning4j (Tweet)
- Learning Neural Networks Using java Libraries (Tweet)
- Create an artificial neural network using the Neuroph Java framework (Tweet)
- Neural Networks WTF by Katharine Beaumont
- Convolutional Neural Networks (CNN)
- Long Short Term Memory (LSTM)
- Recurrent Neural Network (RNN)
- Neural Networks and Decision Trees by Ryutaro Tanno
- predestination: Conway's Game of Life by Samir Talwar | Conway's Game of Life
- Overview of AI Libraries in Java
- Introduction to Machine Learning and Neural Networks for Java Developers
- Tutorial on Collaborative Filtering (CF) in Java – a machine learning technique used by recommendation systems (Tweet)
- The Data Science Process
- Also see Data Science
- Data Science for Java Developers
- Virgilio - Your new Mentor for Data Science E-Learning
- Introduction to Data Science | Other Data Science Stuff related videos
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Also see Tools > Machine Learning Frameworks for a consolidated overview.
- Tribuo | Github | The Oracle Labs Configuration and Utilities Toolkit - Java ML library from Oracle Labs | Tribuo example
- Machine Learning Study Path
- ML for Java Developers
- Java ML Framework: 1 2
- Jena - A free and open source Java framework for building Semantic Web and Linked Data applications
- Weka 3: Machine Learning Software in Java
- Skills for Machine Learning
- Smile - Statistical Machine Intelligence and Learning Engine
- A visual introduction to machine learning
- Abductive Learning: Towards Bridging Machine Learning and Logical Reasoning: Slides | Video | GitHub
- Overview of AI Libraries in Java
- Angel-ML: high-performance distributed machine learning platform (Java-base, Linux Foundation)
- Building Models of Java Code from Source and JAR Files
- Introduction to Machine Learning and Neural Networks for Java Developers
- See Java/JVM in Courses
- See ML on Code/Programm/Source Code
- See Cloud/DevOps/Infra > Performance - to find various ML performance benchmarking suites
- Also see Post model-creation analysis, ML interpretation/explainability
- JFocus: Deep learning with Java | Video |(Tweet)
- Understanding Machine Learning Algorithms with DL4J (Tweet)
- DL4J: Deep Learning for Java | Docs/Guide | Quickstart | Tutorial | Roadmap for Beginners | DL4J Eclipse GitHub | DL4J Examples: GitHub o Semantic site o Examples Tour| Setup Environment | Using DL4J | Support: gitter.im o gitter guidelines o GitHub Issues o Stackoverflow
- DL Workshop at Devoxx UK 2018 by davesnowdon
- [ND4J (Wikipedia)](https://en.wikipedia.org/wiki/ND4J_(software) | ND4J in DL4J
- ND4J: Scientific Computing on the JVM: 1 2
- How to do Deep Learning for Java? | Original post
- Free AI Training - Java-based deep-learning tools to analyze and train data, then send the resulting changes back to the server (Tweet)
- Deep Learning Resources
- Questions when applying Deep Learning
- Deep Learning Use cases
- Overview of AI Libraries in Java
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- PyTorch for Java
- Best AI tools and libraries (Tweet)
- Overview of AI Libraries in Java (Tweet)
- Free AI Learning Resources For Beginners (Twitter)
- Learn about Marvin AI a set of tools, libraries, an embedded server that exposes microservices (Tweet)
- Apache Zeppelin: stairway to notes* haven!
- Efficient Java Matrix Library (EJML) is a linear algebra library for manipulating real/complex/dense/sparse matrices | Java Matrix Benchmark is a tool for evaluating Java linear algebra libraries for speed, stability, and memory usage by Peter Abeles
- Visual Recognition (VisRec) JSR #381
- Onnx Runtime
- Tensorflow Java - optimizers
- Tensorflow Java - optimizers (MNIST)
- Tensorflow SIG
- Apache MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity.
- Tornedo VM
- Learn how to deploy and manage machine learning models (Tweet)
- How to prepare unstructured data for BI and data analytics AI and MachineLearning (Tweet)
- Machine Learning Model Deployment Made Simple: 1 2 (Tweet)
- What are best practices for delivering AI solutions in continuous delivery pipelines? (Tweet)
- Adapt DevOps to cognitive and artificial intelligence systems (Tweet)
- Explore the use of modern Machine Learning and AI techniques in the context of serverless computing (Tweet)
- Disruptive Effects of Cloud Native Machine Learning Systems and Tools (Tweet)
- Introduction to interactive Data Lake Queries (Tweet)
- A Simple Introduction To Data Structures (Tweet)
- Videos of various AI/ML related topics by AI Enterprise
- Real-Time Application of Machine Learning to Geolocation using Spark and Kafka | Slides | Carol's post "Tips and Best Practices to Take Advantage of Spark 2.x"
- Regex resources by Chris Albon
- Linux Command-Line resource by Chris Albon
- TweetyProject - is a collection of various Java libraries that implement approaches to different areas of artificial intelligence
- DSA Roadmap 2024: Complete Learning Guide - Anyone eager to learn DSA from scratch will find here a comprehensive roadmap for learning data structures and algorithms.
See this link for more Java related ML links
- Clojure related ML links
- Scicloj - an open, free and dynamic hub aimed at advancing doing data science, machine learning and numerical computing in Clojure | GitHub | Zulip | Twitter | Youtube | scicloj@gmail.com
See Visualisation
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- Data for Deep Learning
- Practicalli Data Science - data capture, transformation and visualisation - YouTube playlist
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- ⭐ CHEAT SHEET : Supervised and Unsupervised Learning ⭐