NickStrEng's Stars
tensorflow/models
Models and examples built with TensorFlow
nomic-ai/gpt4all
GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.
scikit-learn/scikit-learn
scikit-learn: machine learning in Python
Avik-Jain/100-Days-Of-ML-Code
100 Days of ML Coding
jakevdp/PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
aymericdamien/TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
stefan-jansen/machine-learning-for-trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
marcotcr/lime
Lime: Explaining the predictions of any machine learning classifier
seatgeek/fuzzywuzzy
Fuzzy String Matching in Python
yzhao062/pyod
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
google-deepmind/graphcast
microsoft/promptbase
All things prompt engineering
awslabs/gluonts
Probabilistic time series modeling in Python
louisfb01/best_AI_papers_2021
A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.
BEPb/BEPb
Config files for my GitHub profile.
jakobrunge/tigramite
Tigramite is a python package for causal inference with a focus on time series data. The Tigramite documentation is at
NannyML/The-Little-Book-of-ML-Metrics
The book every data scientist needs on their desk.
miketromba/highest-paying-software-companies
The top 500 highest paying companies based on median software engineer total comp on levels.fyi as of 12/1/23.
ashishpatel26/Amazing-Feature-Engineering
Feature 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.
smousavi05/EQTransformer
EQTransformer, a python package for earthquake signal detection and phase picking using AI.
smousavi05/STEAD
STanford EArthquake Dataset (STEAD):A Global Data Set of Seismic Signals for AI
xdevplatform/Gnip-Trend-Detection
Trend detection algorithms for Twitter time series data
ptocca/VennABERS
Fast implementation of Venn-ABERS probabilistic predictors
mzaffran/AdaptiveConformalPredictionsTimeSeries
amignan/Intro2CATriskModelling
smazzanti/tds_features_important_doesnt_mean_good
xcsf-dev/xcsf
XCSF learning classifier system: rule-based online evolutionary machine learning
UrbsLab/scikit-eLCS
A scikit-learn-compatible Python implementation of eLCS, a supervised learning variant of Learning Classifier Systems
sujithmangalathu/Shear-Wall-Failure-Mode
Failure mode identification of shear walls