Php MlPHP-ML - Machine Learning library for PHP
Stars: ✭ 7,900 (+111.85%)
Free Ai Resources🚀 FREE AI Resources - 🎓 Courses, 👷 Jobs, 📝 Blogs, 🔬 AI Research, and many more - for everyone!
Stars: ✭ 192 (-94.85%)
PyodA Python Toolbox for Scalable Outlier Detection (Anomaly Detection)
Stars: ✭ 5,083 (+36.31%)
HomlrSupplementary material for Hands-On Machine Learning with R, an applied book covering the fundamentals of machine learning with R.
Stars: ✭ 185 (-95.04%)
VizukaExplore high-dimensional datasets and how your algo handles specific regions.
Stars: ✭ 100 (-97.32%)
SusiSuSi: Python package for unsupervised, supervised and semi-supervised self-organizing maps (SOM)
Stars: ✭ 42 (-98.87%)
TadwAn implementation of "Network Representation Learning with Rich Text Information" (IJCAI '15).
Stars: ✭ 43 (-98.85%)
AcceleratorThe Accelerator is a tool for fast and reproducible processing of large amounts of data.
Stars: ✭ 137 (-96.33%)
Efficient AprioriAn efficient Python implementation of the Apriori algorithm.
Stars: ✭ 145 (-96.11%)
Rightmove webscraper.pyPython class to scrape data from rightmove.co.uk and return listings in a pandas DataFrame object
Stars: ✭ 125 (-96.65%)
Pm4py CorePublic repository for the PM4Py (Process Mining for Python) project.
Stars: ✭ 313 (-91.61%)
PzadКурс "Прикладные задачи анализа данных" (ВМК, МГУ имени М.В. Ломоносова)
Stars: ✭ 160 (-95.71%)
DanmfA sparsity aware implementation of "Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection" (CIKM 2018).
Stars: ✭ 161 (-95.68%)
Data Science Resources👨🏽🏫You can learn about what data science is and why it's important in today's modern world. Are you interested in data science?🔋
Stars: ✭ 171 (-95.41%)
Fantasy Basketball Scraping statistics, predicting NBA player performance with neural networks and boosting algorithms, and optimising lineups for Draft Kings with genetic algorithm. Capstone Project for Machine Learning Engineer Nanodegree by Udacity.
Stars: ✭ 146 (-96.08%)
ChefboostA Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4,5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting (GBDT, GBRT, GBM), Random Forest and Adaboost w/categorical features support for Python
Stars: ✭ 176 (-95.28%)
ImodelsInterpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
Stars: ✭ 194 (-94.8%)
Statistical LearningLecture Slides and R Sessions for Trevor Hastie and Rob Tibshinari's "Statistical Learning" Stanford course
Stars: ✭ 223 (-94.02%)
Automlpipeline.jlA package that makes it trivial to create and evaluate machine learning pipeline architectures.
Stars: ✭ 223 (-94.02%)
DeepgraphAnalyze Data with Pandas-based Networks. Documentation:
Stars: ✭ 232 (-93.78%)
Pydataroadopen source for wechat-official-account (ID: PyDataLab)
Stars: ✭ 302 (-91.9%)
Papers Literature Ml Dl Rl AiHighly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning
Stars: ✭ 1,341 (-64.04%)
Ai Learn人工智能学习路线图,整理近200个实战案例与项目,免费提供配套教材,零基础入门,就业实战!包括:Python,数学,机器学习,数据分析,深度学习,计算机视觉,自然语言处理,PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域
Stars: ✭ 4,387 (+17.65%)
MatrixprofileA Python 3 library making time series data mining tasks, utilizing matrix profile algorithms, accessible to everyone.
Stars: ✭ 141 (-96.22%)
GensimTopic Modelling for Humans
Stars: ✭ 12,763 (+242.26%)
DatascienceCurated list of Python resources for data science.
Stars: ✭ 3,051 (-18.18%)
Orange3🍊 📊 💡 Orange: Interactive data analysis
Stars: ✭ 3,152 (-15.47%)
Data Science ToolkitCollection of stats, modeling, and data science tools in Python and R.
Stars: ✭ 169 (-95.47%)
Go Tsnet-Distributed Stochastic Neighbor Embedding (t-SNE) in Go
Stars: ✭ 153 (-95.9%)
DexDex : The Data Explorer -- A data visualization tool written in Java/Groovy/JavaFX capable of powerful ETL and publishing web visualizations.
Stars: ✭ 1,238 (-66.8%)
Amazing Feature EngineeringFeature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.
Stars: ✭ 218 (-94.15%)
Gwu data miningMaterials for GWU DNSC 6279 and DNSC 6290.
Stars: ✭ 217 (-94.18%)
Data Science FreeFree Resources For Data Science created by Shubham Kumar
Stars: ✭ 232 (-93.78%)
LauraeAdvanced High Performance Data Science Toolbox for R by Laurae
Stars: ✭ 203 (-94.56%)
TweetfeelsReal-time sentiment analysis in Python using twitter's streaming api
Stars: ✭ 249 (-93.32%)
Awesome Datascience📝 An awesome Data Science repository to learn and apply for real world problems.
Stars: ✭ 17,520 (+369.83%)
Estadistica Con RApuntes personales sobre estadística, machine learning y lenguaje de programación R
Stars: ✭ 201 (-94.61%)
machine-learningProgramming Assignments and Lectures for Andrew Ng's "Machine Learning" Coursera course
Stars: ✭ 83 (-97.77%)
ml-aiML-AI Community | Open Source | Built in Bharat for the World | Data science problem statements and solutions
Stars: ✭ 32 (-99.14%)
kmeansA simple implementation of K-means (and Bisecting K-means) clustering algorithm in Python
Stars: ✭ 18 (-99.52%)
UrsUniversal Reddit Scraper - A comprehensive Reddit scraping command-line tool written in Python.
Stars: ✭ 275 (-92.63%)
Tsrepr TSrepr: R package for time series representations
Stars: ✭ 75 (-97.99%)
Tsv UtilseBay's TSV Utilities: Command line tools for large, tabular data files. Filtering, statistics, sampling, joins and more.
Stars: ✭ 1,215 (-67.42%)