Return to Machine Learning - Deep Learning, Ruby Deep Learning, DataOps-MLOps-DevOps, Data Science, Ruby Official Glossary, Ruby Topics, Ruby, Ruby DevOps - Ruby SRE, Ruby Data Science - Ruby DataOps, Ruby MLOps
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. Advances in the field of deep learning have allowed neural networks 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. 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 (PAC) learning provides a framework for describing machine learning.
Ruby: Ruby Fundamentals, Ruby Inventor - Ruby Language Designer: Yukihiro Matsumoto in 1995; Ruby scripting, Rails, RubyGems, Ruby keywords, Ruby Built-In Data Types, Ruby data structures - Ruby algorithms, Ruby syntax, Ruby OOP - Ruby design patterns, Ruby for Chef, Ruby for Puppet, Ruby on Linux, Ruby on macOS, Ruby on Windows, Ruby installation, Ruby containerization, Ruby configuration, Ruby compiler - Ruby interpreter (Matz's Ruby Interpreter or Ruby MRI, also called CRuby), Ruby IDEs (RubyMine), Ruby development tools, Ruby DevOps - Ruby SRE, Ruby data science - Ruby DataOps, Ruby machine learning, Ruby deep learning, Functional Ruby, Ruby concurrency, Ruby history, Ruby bibliography, Ruby glossary, Ruby topics, Ruby courses, Ruby Standard Library, Ruby libraries, Ruby frameworks (Ruby on Rails), Ruby research, Ruby GitHub, Written in Ruby, Ruby popularity, Ruby Awesome list, Ruby Versions. (navbar_ruby)
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)
© 1994 - 2024 Cloud Monk Losang Jinpa or Fair Use. Disclaimers
SYI LU SENG E MU CHYWE YE. NAN. WEI LA YE. WEI LA YE. SA WA HE.