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Machine learning algorithms
Machine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches. Machine learning approaches have been applied to large language models, computer vision, speech recognition, email filtering, agriculture and medicine, where it is too costly to develop algorithms to perform the needed tasks.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 through unsupervised learning.ML is known in its application across business problems under the name predictive analytics. Although not all machine learning is statistically-based, computational statistics is an important source of the field's methods.
Topics
- Viterbi coding
- Symmetric group S4; Steinhaus-Johnson-Trotter algorithm
- Videos of algorithms
- Smith–Waterman algorithm
- Sort algorithms
- Shortest remaining time
- Simulated annealing
- Self-stabilization
- Shortest job next
- Round-robin algorithm
- Robot localization
- Quality images of algorithms
- Recursive algorithms
- Peliculas algorithm
- PageRank
- Needleman–Wunsch algorithm
- Leaky bucket
- Greedy algorithms
- CYK algorithm
- Data compression
- Control statement
- Computer arithmetic algorithms
- Computational geometry
- Cholesky decomposition
- Calendar algorithms
- Checksum
- Cache algorithm
- Arithmetic algorithms
- Algorismus
- Reed-Solomon error correction
- Check digit
- Graph algorithms
- ORES
- Concurrent algorithms
- Flow charts
- Pattern matching
- Algorithms on strings
- Animations of machine learning
- Bioinformatics algorithms
- Combinatorial algorithms
- Artificial intelligence training data
- Vowpal Wabbit
- Wikimania 2016 – Lessons learned building machine learning models for Wikidata
- User:Perellonieto
- Vapnik-Chervonenkis dimension
- Videos of machine learning
- Thought cloning in AI
- Underfitting
- Structured prediction
- Support vector machine
- Statistical classification
- Overfitting
- Probabilistic Graphical Model
- Reinforcement Learning
- Markov models
- Neural-Style
- Machine learning research
- Machine learning task
- Inductive logic programming
- Kernel methods for machine learning
- Data spirals
- Classification algorithms
- Artificial neural networks
- Evolutionary algorithms
- Regex
- Automated pattern recognition
- Media from Algorithms for Molecular Biology
- Statistical algorithms
- Computer graphic algorithms
- Hough transform
- Computational number theory
- Programming
- Algorithms
- Machine Learning
- Electronic Engineering