Ml Workspace🛠 All-in-one web-based IDE specialized for machine learning and data science.
Stars: ✭ 2,337 (+446.03%)
Eli5A library for debugging/inspecting machine learning classifiers and explaining their predictions
Stars: ✭ 2,477 (+478.74%)
Hyperlearn50% faster, 50% less RAM Machine Learning. Numba rewritten Sklearn. SVD, NNMF, PCA, LinearReg, RidgeReg, Randomized, Truncated SVD/PCA, CSR Matrices all 50+% faster
Stars: ✭ 1,204 (+181.31%)
Hep mlMachine Learning for High Energy Physics.
Stars: ✭ 133 (-68.93%)
VirgilioVirgilio is developed and maintained by these awesome people.
You can email us virgilio.datascience (at) gmail.com or join the Discord chat.
Stars: ✭ 13,200 (+2984.11%)
ExplainxExplainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code.
Stars: ✭ 196 (-54.21%)
Scikit Learn VideosJupyter notebooks from the scikit-learn video series
Stars: ✭ 3,254 (+660.28%)
Mlatimperial2017Materials for the course of machine learning at Imperial College organized by Yandex SDA
Stars: ✭ 71 (-83.41%)
PbpythonCode, Notebooks and Examples from Practical Business Python
Stars: ✭ 1,724 (+302.8%)
Pymc Example ProjectExample PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.
Stars: ✭ 90 (-78.97%)
Bert Sklearna sklearn wrapper for Google's BERT model
Stars: ✭ 182 (-57.48%)
ImodelsInterpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
Stars: ✭ 194 (-54.67%)
PqkmeansFast and memory-efficient clustering
Stars: ✭ 189 (-55.84%)
CodeCompilation of R and Python programming codes on the Data Professor YouTube channel.
Stars: ✭ 287 (-32.94%)
Fraud DetectionCredit Card Fraud Detection using ML: IEEE style paper + Jupyter Notebook
Stars: ✭ 58 (-86.45%)
MlkatasA series of self-correcting challenges for practicing your Machine Learning and Deep Learning skills
Stars: ✭ 58 (-86.45%)
Text Analytics With PythonLearn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer.
Stars: ✭ 1,132 (+164.49%)
Islr With PythonIntroduction to Statistical Learning with R을 Python으로
Stars: ✭ 73 (-82.94%)
Ml Starter PackA collection of Machine Learning algorithms written from sctrach.
Stars: ✭ 72 (-83.18%)
Ds and ml projectsData Science & Machine Learning projects and tutorials in python from beginner to advanced level.
Stars: ✭ 56 (-86.92%)
Dat8General Assembly's 2015 Data Science course in Washington, DC
Stars: ✭ 1,516 (+254.21%)
DtreevizA python library for decision tree visualization and model interpretation.
Stars: ✭ 1,857 (+333.88%)
Dive Into Machine LearningDive into Machine Learning with Python Jupyter notebook and scikit-learn! First posted in 2016, maintained as of 2021. Pull requests welcome.
Stars: ✭ 10,810 (+2425.7%)
SelfdrivingcarA collection of all projects pertaining to different layers in the SDC software stack
Stars: ✭ 107 (-75%)
Practical Machine Learning With PythonMaster the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
Stars: ✭ 1,868 (+336.45%)
Sklearn BenchmarksA centralized repository to report scikit-learn model performance across a variety of parameter settings and data sets.
Stars: ✭ 194 (-54.67%)
Bet On SibylMachine Learning Model for Sport Predictions (Football, Basketball, Baseball, Hockey, Soccer & Tennis)
Stars: ✭ 190 (-55.61%)
Machine Learning With PythonPractice and tutorial-style notebooks covering wide variety of machine learning techniques
Stars: ✭ 2,197 (+413.32%)
Text ClassificationMachine Learning and NLP: Text Classification using python, scikit-learn and NLTK
Stars: ✭ 239 (-44.16%)
Sklearn EvaluationMachine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking and Jupyter notebook analysis.
Stars: ✭ 294 (-31.31%)
Deepbayes 2018Seminars DeepBayes Summer School 2018
Stars: ✭ 1,021 (+138.55%)
Machine Learningnotebooks with example for machine learning examples
Stars: ✭ 45 (-89.49%)
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 (-49.07%)
ZatZeek Analysis Tools (ZAT): Processing and analysis of Zeek network data with Pandas, scikit-learn, Kafka and Spark
Stars: ✭ 303 (-29.21%)
ThesemicolonThis repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.
Stars: ✭ 345 (-19.39%)