tonsider

tonsider's Stars

• onnx/onnx

  Open standard for machine learning interoperability

  Language:Python18.2k3.7k

• onnx/tutorials

  Tutorials for creating and using ONNX models

  Language:Jupyter Notebook3.4k633

• goabstract/Marketing-for-Engineers

  A curated collection of marketing articles & tools to grow your product.

  12.8k925

• huggingface/transformers

  🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

  Language:Python137k27.4k

• Netflix/metaflow

  Open Source AI/ML Platform

  Language:Python8.4k778

• MathiasGruber/AI-Paper-References

  References for read papers + relevant links

  81

• PacktPublishing/Machine-Learning-with-Scikit-learn

  Machine Learning with Scikit-learn by Packt Publishing

  Language:Jupyter Notebook105

• ageron/handson-ml

  ⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.

  Language:Jupyter Notebook25.2k12.9k

• sat28/githubcommit

  A jupyter notebook extension enabling users push ipython notebooks to a git repo

  Language:Python12875

• BenLangmead/ads1-slides

  Slides for Algorithms for DNA Sequencing Coursera class

  320222

• BenLangmead/ads1-notebooks

  Copies of notebooks used in the practical sessions for Algorithms for DNA Sequencing

  375367

• pyenv/pyenv

  Simple Python version management

  Language:Roff40k3.1k

• jadianes/spark-py-notebooks

  Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks

  Language:Jupyter Notebook1.6k916

• jadianes/spark-movie-lens

  An on-line movie recommender using Spark, Python Flask, and the MovieLens dataset

  Language:Jupyter Notebook821394

• hnsl/colpivot

  Dynamic row to column pivotation/transpose in Postgres made simple.

  Language:PLpgSQL20955

• 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 ;)

  Language:Jupyter Notebook26.9k7.9k

• markdregan/Bayesian-Modelling-in-Python

  A python tutorial on bayesian modeling techniques (PyMC3)

  Language:Jupyter Notebook2.5k414

• pymc-devs/pymc

  Bayesian Modeling and Probabilistic Programming in Python

  Language:Python8.8k2k

• pjarnhus/DataScienceGym

  A series of little puzzles and training exercises aimed at improving python knowledge for data science

  Language:Jupyter Notebook92

• daviddao/awful-ai

  😈Awful AI is a curated list to track current scary usages of AI - hoping to raise awareness

  7k233

• tecladocode/rest-apis-flask-python

  Projects and e-book for our course, REST APIs with Flask and Python

  Language:Python1.4k1.5k

• larsenwork/postcss-easing-gradients

  PostCSS plugin to create smooth linear-gradients that approximate easing functions.

  Language:JavaScript93222

• philipperemy/cocktails

  Generate the best cocktail ever with Machine Learning !

  Language:Python74

• michalfaber/keras_Realtime_Multi-Person_Pose_Estimation

  Keras version of Realtime Multi-Person Pose Estimation project

  Language:Jupyter Notebook780373

• graphql/graphiql

  GraphiQL & the GraphQL LSP Reference Ecosystem for building browser & IDE tools.

  Language:TypeScript16.2k1.7k

• NSchrading/redditDataExtractor

  The reddit Data Extractor is a cross-platform GUI tool for downloading almost any content posted to reddit. Downloads from specific users, specific subreddits, users by subreddit, and with filters on the content is supported. Some intelligence is built in to attempt to avoid downloading duplicate external content.

  Language:Python23230

• PAIR-code/facets

  Visualizations for machine learning datasets

  Language:Jupyter Notebook7.4k886

• tantlab/table2net

  Language:JavaScript2

• tantlab/tools

  A portal for digital methods tools

  Language:CSS22

• leriomaggio/deep-learning-keras-tensorflow

  Introduction to Deep Neural Networks with Keras and Tensorflow

  Language:Jupyter Notebook3k1.3k