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Ruby 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. Recently, artificial neural networks have been able to surpass many previous approaches in performance.
ML finds application in many fields, including natural language processing, computer vision, speech recognition, email filtering, agriculture, and medicine. When applied to business problems, it is known under the name predictive analytics. Although not all machine learning is statistically based, computational statistics is an important source of the field's methods.
The mathematical foundations of ML are provided by mathematical optimization (mathematical programming) methods. Data mining is a related (parallel) field of study, focusing on exploratory data analysis (EDA) through unsupervised learning.
From a theoretical viewpoint, probably approximately correct (PAC) learning provides a framework for describing machine learning.
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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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