User:Rajivmah/Books/Machine Learning

Machine Learning

Really Artificial Intelligence !!

Natural language processing

Tf–idf

Locality-sensitive hashing

Word2vec

Hierarchical Dirichlet process

Latent semantic analysis

Latent Dirichlet allocation

Linear discriminant analysis

Cosine similarity

Word embedding

Document-term matrix

Language model

Thought vector

Vector space model

Parsing

Sentiment analysis

GloVe (machine learning)

Deeplearning4j

Principal component analysis

T-distributed stochastic neighbor embedding

Brown clustering

Hidden Markov model

Kernel method

Feature learning

Feature engineering

Multilayer perceptron

Autoencoder

Independent component analysis

Regularization (mathematics)

Radial basis function

Radial basis function network

Named-entity recognition

Eigenvalues and eigenvectors

Nonlinear dimensionality reduction

Restricted Boltzmann machine

Boltzmann machine

Stochastic gradient descent

Vector quantization

Feature extraction

Deep learning

Basis function

K-means clustering

NP-hardness

Greedy algorithm

Artificial neural network

Feature selection

Machine learning

Dimensionality reduction

Cluster analysis

Gradient descent

Unsupervised learning

Supervised learning

Overfitting

Singular value decomposition

Pattern recognition

Support vector machine

Multilinear subspace learning

Vector space

Regression analysis

Semi-supervised learning

Dot product

Correlation and dependence

Curse of dimensionality

Artificial intelligence

K-nearest neighbors algorithm

Structured prediction

Anomaly detection

Reinforcement learning

Statistical classification

Email filtering

Multi-label classification

Topic model

Information retrieval

Connectionism

Backpropagation

Knowledge extraction

ECML PKDD

Bias–variance tradeoff

Decision tree learning

Inductive logic programming

Functional programming

Bayesian network

Graphical model

Similarity learning

Recommender system

Sparse dictionary learning

Strong NP-completeness

K-SVD

Ensemble averaging (machine learning)

Part-of-speech tagging

Logistic regression

Multinomial logistic regression

Probit model

Perceptron

Variable kernel density estimation

Boosting (machine learning)

Random forest

Learning vector quantization

No free lunch in search and optimization

Precision and recall

Receiver operating characteristic

Uncertainty coefficient

Document classification

Stochastic grammar

List of datasets for machine learning research

Hierarchical clustering

Multivariate normal distribution

Expectation–maximization algorithm

DBSCAN

OPTICS algorithm

Biclustering

HCS clustering algorithm

Fuzzy clustering

Clustering high-dimensional data

UPGMA

Lloyd's algorithm

Probability distribution

Normal distribution

Deterministic algorithm

Single-linkage clustering

Mean shift

Kernel density estimation

BIRCH

Canopy clustering algorithm

Correlation clustering

SUBCLU

Basic sequential algorithmic scheme

Davies–Bouldin index

Dunn index

Silhouette (clustering)

Constrained clustering

Rand index

F1 score

Jaccard index

Fowlkes–Mallows index

Mutual information

Confusion matrix

Balanced clustering

Conceptual clustering

Consensus clustering

Data stream clustering

Sequence clustering

Spectral clustering

Nearest neighbor search

Neighbourhood components analysis

Latent class model

Multidimensional scaling

Determining the number of clusters in a data set

Parallel coordinates

Structured data analysis (statistics)

Cluster-weighted modeling

Kernel principal component analysis

Local tangent space alignment

Isomap

Diffusion map

Semidefinite embedding

Canonical correlation

Feature (machine learning)

Embedding

Random projection

Semantic mapping (statistics)

Multilinear principal component analysis

Hyperparameter optimization

Weighted correlation network analysis

Sufficient dimension reduction

Topological data analysis

Outlier

Local outlier factor

Association rule learning

Ensemble learning

Random subspace method

Novelty detection

Change detection

Intrusion detection system

Misuse detection

Markov logic network

Case-based reasoning

Conditional random field

Viterbi algorithm

Linear classifier

Structured support vector machine

Recurrent neural network

Markov decision process

Markov chain

Probabilistic neural network

Time delay neural network

Regulatory feedback network

Feedforward neural network

Hopfield network

Echo state network

Long short-term memory

Self-organizing map

Stochastic neural network

Neocognitron

ADALINE

Convolutional neural network

Modular neural network

Committee machine

Autoassociative memory

DeepMind

Holographic associative memory

Turing machine

Adaptive resonance theory

Hierarchical temporal memory

Instantaneously trained neural networks

Spiking neural network

Counterpropagation network

Physical neural network

Optical neural network

Fuzzy logic

List of machine learning concepts

Averaged one-dependence estimators

Group method of data handling

Kriging

Instance-based learning

Probably approximately correct learning

Ripple-down rules

Logistic model tree

Ensembles of classifiers

Bootstrap aggregating

Level of measurement

Information Fuzzy Networks

Analysis of variance

Naive Bayes classifier

Quadratic classifier

C4.5 algorithm

ID3 algorithm

Generative topographic map

Information bottleneck method

Apriori algorithm

Co-training

Temporal difference learning

Q-learning

Learning automata

State-Action-Reward-State-Action

List of artificial intelligence projects

Data pre-processing

Deep belief network

Fictitious play

Learning classifier system

Optimal control

Dynamic treatment regime

Error-driven learning