CodeBrowser / npm / machine-learning
machine-learning@0.17.0
// TypeScript & JavaScript machine learning library
$ npm install machine-learning
downloads/wk
51
license
MIT
version
0.17.0
published
Jun 11, 2026
What is machine-learning?
A comprehensive TypeScript and JavaScript library implementing a wide range of machine learning algorithms, from foundational techniques like linear regression and k-means clustering to advanced methods such as neural networks, deep reinforcement learning, and generative models. Developers can use this package to add ML capabilities to JavaScript applications without requiring external dependencies or Python integrations, making it useful for tasks like classification, anomaly detection, time series forecasting, and natural language processing directly in Node.js or browser environments.
Keywords
#machine learning #artificial intelligence #matrix #neural network #linear regression #logistic regression #nearest neighbors #k-nearest neighbors #k nearest neighbors #k-NN #KNN #naive bayes #decision tree #random forest #gradient boosting #ensemble #support vector machine #svm #kernel #classification #k-means #clustering #hierarchical clustering #agglomerative #dendrogram #dbscan #density clustering #anomaly detection #pca #principal component analysis #dimensionality reduction #outlier detection #mahalanobis #association rules #apriori #market basket analysis #recommender #collaborative filtering #matrix factorization #time series #forecasting #exponential smoothing #perceptron #convolutional neural network #cnn #deep learning #computer vision #recurrent neural network #rnn #embeddings #nlp #transformer #attention #self-attention #reinforcement learning #multi-armed bandit #bandit #explore exploit #epsilon-greedy #ucb #contextual bandit #linucb #q-learning #markov decision process #temporal difference #gridworld #deep reinforcement learning #deep q-network #dqn #experience replay #autoencoder #representation learning #denoising #bottleneck #variational autoencoder #vae #generative model #generative ai #bayesian #bayesian regression #uncertainty #probabilistic
Maintainers
erikgerrits