bachaudhry

applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

DeepSpeech

DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.

datasets

🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools

prophet

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

awesome-mlops

A curated list of references for MLOps

pandas_exercises

Practice your pandas skills!

tokenizers

💥 Fast State-of-the-Art Tokenizers optimized for Research and Production

awesome-NeRF

A curated list of awesome neural radiance fields papers

zenml

ZenML 🙏: The bridge between ML and Ops. https://zenml.io.

spark-nlp

State of the Art Natural Language Processing

neural_prophet

NeuralProphet: A simple forecasting package

lit

The Learning Interpretability Tool: Interactively analyze ML models to understand their behavior in an extensible and framework agnostic interface.

Papers-Literature-ML-DL-RL-AI

Highly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning

DS-Career-Resources

Compilation of resources for aspiring data scientists

stylegan2-ada

StyleGAN2 with adaptive discriminator augmentation (ADA) - Official TensorFlow implementation

svoice

We provide a PyTorch implementation of the paper Voice Separation with an Unknown Number of Multiple Speakers In which, we present a new method for separating a mixed audio sequence, in which multiple voices speak simultaneously. The new method employs gated neural networks that are trained to separate the voices at multiple processing steps, while maintaining the speaker in each output channel fixed. A different model is trained for every number of possible speakers, and the model with the largest number of speakers is employed to select the actual number of speakers in a given sample. Our method greatly outperforms the current state of the art, which, as we show, is not competitive for more than two speakers.

madgrad

MADGRAD Optimization Method

mordecai

Full text geoparsing as a Python library

high-fidelity-generative-compression

Pytorch implementation of High-Fidelity Generative Image Compression + Routines for neural image compression

MITx_6.86x

Notes of MITx 6.86x - Machine Learning with Python: from Linear Models to Deep Learning

CompStats

Code for a workshop on statistical interference using computational methods in Python.

htsprophet

Hierarchical Time Series Forecasting using Prophet

leetcode

The mediocre solutions to leetcode problems using Python

MLProject-ChurnPrediction

scikit-hts-examples

Example usage of scikit-hts

causalinf_ex_elasticity

A full example for causal inference on real-world retail data, for elasticity estimation

Statistics-for-Data-Science-using-Python

Using Python, learn statistical and probabilistic approaches to understand and gain insights from data. Learn statistical concepts that are very important to Data science domain and its application using Python. Learn about Numpy, Pandas Data Frame.

crystalvalue

ziln_cltv

A python package to train & evaluate Customer Lifetime Value(CLTV) models using Neural Networks & ZILN loss(developed by google)

customer-lifetime-value-contractual-or-non-contractual-relationship

Machine Learning to determine Customer Lifetime Value in a contractual or non-contractual setting.