Maksim Lebedev's starred repositories
amazon-sagemaker-examples
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
computer-science
:mortar_board: Path to a free self-taught education in Computer Science!
data-science
:bar_chart: Path to a free self-taught education in Data Science!
CS224n-Resource
CS224n Assignment & Readings
socceraction
Convert soccer event stream data to SPADL and value player actions using VAEP or xT
TemporalBallDetection
Official implementation of the paper: Utilizing Temporal Information in Deep Convolutional Network for Efficient Soccer Ball Detection and Tracking
SoccerNet-code
SoccerNet: A Scalable Dataset for Action Spotting in Soccer Videos
mapping-match-events-in-Python
Luca Pappalardos code for working with and plotting Wyscout data
sample-data
Metrica Sports sample tracking and event data
ThinkBayes2
Text and code for the forthcoming second edition of Think Bayes, by Allen Downey.
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 ;)
CharCnn_Keras
The implementation of text classification using character level convoultion neural networks using Keras
deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Multicore-TSNE
Parallel t-SNE implementation with Python and Torch wrappers.
deep-image-prior
Image restoration with neural networks but without learning.
lectures-labs
Slides and Jupyter notebooks for the Deep Learning lectures at Master Year 2 Data Science from Institut Polytechnique de Paris
ProbAndStats-PyDataNYC2019
Introduction to Probability and Statistics
sentence-transformers
Multilingual Sentence & Image Embeddings with BERT
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 ;)
AdaGram.jl
Adaptive Skip-gram implementation in Julia
online-hdp
Online inference for the Hierarchical Dirichlet Process. Fits hierarchical Dirichlet process topic models to massive data. The algorithm determines the number of topics.