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Java Machine Learning
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- Snippet from Wikipedia: Machine learning
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. Within a subdiscipline in machine learning, advances in the field of deep learning have allowed neural networks, a class of statistical algorithms, to surpass many previous machine learning approaches in performance.
ML finds application in many fields, including natural language processing, computer vision, speech recognition, email filtering, agriculture, and medicine. The application of ML to business problems is known as predictive analytics.
Statistics and mathematical optimization (mathematical programming) methods comprise the foundations of machine learning. Data mining is a related field of study, focusing on exploratory data analysis (EDA) via unsupervised learning.
From a theoretical viewpoint, probably approximately correct learning provides a framework for describing machine learning.
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Java: Java Fundamentals, Java Inventor - Java Language Designer: James Gosling of Sun Microsystems, Java Docs, JDK, JVM, JRE, Java Keywords, JDK 17 API Specification, java.base, Java Built-In Data Types, Java Data Structures - Java Algorithms, Java Syntax, Java OOP - Java Design Patterns, Java Installation, Java Containerization, Java Configuration, Java Compiler, Java Transpiler, Java IDEs (IntelliJ - Eclipse - NetBeans), Java Development Tools, Java Linter, JetBrains, Java Testing (JUnit, Hamcrest, Mockito), Java on Android, Java on Windows, Java on macOS, Java on Linux, Java DevOps - Java SRE, Java Data Science - Java DataOps, Java Machine Learning, Java Deep Learning, Functional Java, Java Concurrency, Java History,
Java Bibliography (Effective Java, Head First Java, Java - A Beginner's Guide by Herbert Schildt, Java Concurrency in Practice, Clean Code by Robert C. Martin, Java - The Complete Reference by Herbert Schildt, Java Performance by Scott Oaks, Thinking in Java, Java - How to Program by Paul Deitel, Modern Java in Action, Java Generics and Collections by Maurice Naftalin, Spring in Action, Java Network Programming by Elliotte Rusty Harold, Functional Programming in Java by Pierre-Yves Saumont, Well-Grounded Java Developer, Second Edition, Java Module System by Nicolai Parlog
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Machine Learning: ML Fundamentals, ML Inventor: Arthur Samuel of IBM 1959 coined term Machine Learning. Synonym Self-Teaching computers from 1950s. Experimental AI “Learning Machine” called Cybertron in early 1960s by Raytheon Company; ChatGPT, NLP, GAN, ML, DL - Deep learning - Python Deep learning, MLOps, Python machine learning (sci-kit, OpenCV, TensorFlow, PyTorch, Keras, NumPy, NLTK, SciPy, sci-kit learn, Seaborn, Matplotlib), Cloud ML (AWS ML, Azure ML, Google ML-GCP ML-Google Cloud ML, IBM ML, Apple ML), C++ Machine Learning, C# Machine Learning, Golang Machine Learning, Java Machine Learning, JavaScript Machine Learning, Julia Machine Learning, Kotlin Machine Learning, R Machine Learning, Ruby Machine Learning, Rust Machine Learning, Scala Machine Learning, Swift Machine Learning, ML History, ML Bibliography, Manning AI-ML-DL-NLP-GAN Series, ML Glossary, ML Topics, ML Courses, ML Libraries, ML Frameworks, ML GitHub, ML Awesome List. (navbar_ml - See also navbar_dl, navbar_nlp, navbar_chatgpt and navbar_ai, navbar_tensorflow)
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