AI Without Math

AI Without Math

Making AI and ML comprehensible

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Clustering Convolutional neural networks Cross-validation Expert systems Kernels Linear regression Machine learning process Naive Bayes algorithm Neural networks Rational agents

Recurrent neural networks

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Articles wanted - specific examples

Active learning Algorithmic bias Anomaly detection ANOVA Association rules Associative classifier Autoencoder Summarization Taxonomy construction AutoML Backpropagation Bag-of-words model Batch learning Bayesian Belief Network (BBN) Bayesian Network (BN) Bias-variance dilemma Boosting Bootstrap aggregating Canonical correlation analysis (CCA) Case-based reasoning Catastrophic interference Classification and regression tree (CART) Cluster analysis Collaborative filtering Computer vision Concept drift Conceptual clustering Conditional decision tree Conditional random field (CRF) Confusion matrix Content-based filtering Convolutional neural network Cross-validation (statistics) Curse of dimensionality Data preprocessing DBSCAN Decision tree Deep belief networks (DBNs) Deep Boltzmann Machine (DBM) Deep Convolutional neural networks Deep learning Dialog system Dimensionality reduction Eager learning Early stopping Ensemble averaging Ensemble learning Expectation propagation Expectation-maximization (EM) Explanation-based learning Facial recognition system Factor analysis Feature (machine learning) Feature engineering Feature extraction Feature hashing Feature learning Feature scaling Feature selection Feedforward neural network Forward–backward algorithm Gaussian Naive Bayes Gaussian process regression Generative Adversarial Networks Generative model Generative topographic map GeneRec Genetic algorithm Genetic Algorithm for Rule Set Production Glossary of artificial intelligence Gradient boosted decision tree (GBDT) Gradient boosting machine (GBM) Grammar checker Grammar induction Granular computing Graph-based methods Graphical models Graphics processing unit Group method of data handling (GMDH) Growing self-organizing map H2O Handwriting recognition HEXQ Hidden Markov Hidden Markov model (HMM) Hidden Markov models Hierarchical classifier Hierarchical clustering Hierarchical Clustering Hierarchical hidden Markov model Hierarchical k-means clustering Hierarchical temporal memory Highway network Hybrid recommender systems (Collaborative and content-based filtering) Hyper basis function network Hyperparameter (machine learning) Hyperparameter optimization ID3 algorithm IDistance Image recognition Inauthentic text Independent component analysis (ICA) Inductive bias Inductive logic programming Inductive probability Inductive programming Inferential theory of learning Information bottleneck method Information fuzzy networks (IFN) Instance selection Instance-based algorithm Instance-based learning Instantaneously trained neural networks Inverted pendulum – balance and equilibrium system. Isotropic position Iterative Dichotomiser 3 (ID3) Journal of Machine Learning Research K-means clustering K-medians k-nearest neighbor k-nearest neighbors K-nearest neighbors algorithm K-nearest neighbors algorithm (KNN) k-nearest neighbors classification (k-NN) Kernel density estimation Kernel embedding of distributions Kernel methods for vector output Kernel principal component analysis Knowledge integration Labeled data Language recognition Large margin nearest neighbor Lazy learning Leabra Learnable function class Learning Automata Learning automaton Learning curve (machine learning) learning DeepDream Learning rate Learning to rank Learning Vector Quantization Learning vector quantization (LVQ) Learning with errors Least Absolute Shrinkage and Selection Operator (LASSO) Least-angle regression (LARS) Leave-one-out error Life-time of correlation Linde–Buzo–Gray algorithm Linear classifier Linear discriminant analysis (LDA) Linear predictor function Linear regression Naive Linear separability List of datasets for machine-learning research Local case-control sampling Local outlier factor Logic learning machine Logistic Model Tree Logistic regression LogitBoost Long short-term memory (LSTM) Low-density separation M-Theory (learning framework) Machine learning Machine Learning (journal) Machine learning algorithm Machine learning algorithms Machine learning control Machine learning framework Machine learning frameworks Machine learning hardware Machine learning in bioinformatics Machine learning in physics Machine learning in video games Machine learning libraries Machine learning library Machine learning method (list) Machine learning methods Machine learning tools Machine learning tools (list) Machine translation Manifold alignment Manifold regularization Matrix regularization Matthews correlation coefficient Mean-shift Meta learning Meta learning (computer science) Metadata Microsoft Azure Machine Learning Studio Minimum message length (decision trees, decision graphs, etc.) Minimum redundancy feature selection Mixture model Mixture of experts mlpack Model-free (reinforcement learning) Mountain car problem Movidius Multi-armed bandit Multi-label classification Multi-task learning Multidimensional scaling (MDS) Multilayer perceptron Multilinear principal component analysis Multilinear subspace learning Multimodal sentiment analysis Multinomial logistic regression Multinomial Naive Bayes Multiple instance learning Multiple kernel learning Multiple-instance learning Multiplicative weight update method Multitask optimization Multivariate adaptive regression spline Multivariate adaptive regression splines (MARS) Naive Bayes Naive Bayes classifier Native-language identification Natural language processing (NLP) Nature Machine Intelligence Nearest Neighbor Algorithm Nearest neighbor search Neural modeling fields Non-negative matrix factorization Non-negative matrix factorization (NMF) Novelty detection Occam learning Offline learning Online learning Online machine learning Open source machine learning frameworks OpenAI Five OpenNN Optical character recognition OPTICS algorithm Ordinal classification Ordinary least squares regression (OLSR) Other machine learning methods and problems Out-of-bag error Outline of machine learning Overfitting PAC learning Paraphrasing (computational linguistics) Parity learning Partial least squares regression (PLSR) Pattern language (formal languages) Pattern recognition Perceptron Predictive learning Predictive state representation Preference learning Prefrontal cortex basal ganglia working memory Principal component analysis (PCA) Principal component regression (PCR) Prior knowledge for pattern recognition Proactive learning Proaftn Probabilistic classifier Probability matching Probably approximately correct learning (PAC) learning Product of experts Programming by example Projection pursuit Proprietary machine learning frameworks Proximal gradient methods for learning PVLV PyTorch Q-learning Qloo Quadratic classifiers Quadratic unconstrained binary optimization Quantum machine learning Query-level feature Question answering Quickprop Rademacher complexity Radial basis function network RAMnets Random forest Random Forest Random Forests Random indexing Random projection Randomized weighted majority algorithm Recommendation system Recurrent neural network Regression Regression analysis Regularization algorithm Reinforcement learning Reinforcement Learning Relational data mining Relevance vector machine (RVM) Repeated incremental pruning to produce error reduction (RIPPER) Representer theorem Restricted Boltzmann machine Ridge regression Right to explanation Ripple down rules, a knowledge acquisition methodology Robot learning Rprop Rule induction Rule-based machine learning Sammon mapping Sample complexity Savi Technology Scikit-learn Search engine Search engine optimization Self-organizing map Self-organizing map (SOM) Semantic analysis (machine learning) Semantic folding Semi-supervised learning Sequence labeling Similarity learning Single-linkage clustering Skill chaining SLIQ Social Engineering Solomonoff's theory of inductive inference Sparse dictionary learning Sparse PCA Speech recognition Speech synthesis Spike-and-slab regression SPRINT Stability (learning theory) Stacked Auto-Encoders Stacked Generalization (blending) State–action–reward–state–action State–action–reward–state–action (SARSA) Statistical classification Statistical learning Statistical learning theory Statistical relational learning Stepwise regression Stochastic block model Stochastic gradient descent Structural risk minimization Structured kNN Structured prediction Structured sparsity regularization Subclass reachability Supervised learning Support vector machine Support vector machine (SVM) Support vector machines Symbolic machine learning algorithms T-distributed stochastic neighbor embedding t-distributed stochastic neighbor embedding (t-SNE) Temporal difference (TD) Temporal difference learning Temporal difference learning (TD) Tensor processing unit TensorFlow Term frequency–inverse document frequency (tf–idf) Text mining Text simplification The Master Algorithm Theano Time series Timeline of machine learning Torch Training, validation, and test sets Transduction Transduction (machine learning) Transfer learning Trax Retail Types of machine learning algorithms Ugly duckling theorem Uncertain data Uniform convergence in probability Universal portfolio algorithm Unsupervised learning User behavior analytics Validation set Vanishing gradient problem VaultML VC theory Vector Quantization Version space learning Vision processing unit Waifu2x Wake-sleep algorithm Weak supervision Weighted majority algorithm (machine learning) Word2vec