behnamh's Stars
joelmiller/DynamicProcessesOnNetworks
dask/dask-examples
Easy-to-run example notebooks for Dask
guipsamora/pandas_exercises
Practice your pandas skills!
rougier/from-python-to-numpy
An open-access book on numpy vectorization techniques, Nicolas P. Rougier, 2017
jphall663/interpretable_machine_learning_with_python
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
ogrisel/text-mining-class
Introduction to web scraping and text mining
feast-dev/feast
The Open Source Feature Store for Machine Learning
pridiltal/oddstream
oddstream {Outlier Detection in Data STREAMs} :fish: :fish: :fish: :fish: :tropical_fish: :fish: :fish: :fish: :fish: :fish: :fish: :fish: :fish: :fish::fish:
AileenNielsen/TimeSeriesAnalysisWithPython
ctgk/PRML
PRML algorithms implemented in Python
adamjm/powerai-deployment
A PowerAI Docker Image and Deployment Config
ksatola/Computational-Statistics
An introduction to computational statistics with examples and comparison to analytical methods
twitter/AnomalyDetection
Anomaly Detection with R
eriklindernoren/ML-From-Scratch
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
ML-on-structures/graph-lstm
LSTM implementation, and multi-layer LSTMs for learning on graph neighborhoods
khundman/telemanom
A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.
RangeNetworks/OpenBTS-UMTS
3G UMTS Data Radio Access Network Node
papers-we-love/papers-we-love
Papers from the computer science community to read and discuss.
fchollet/deep-learning-models
Keras code and weights files for popular deep learning models.
hadley/r4ds
R for data science: a book