che-kir

Uber-Rider-Churn-Analysis

Uber is interested in predicting rider retention. To help explore this question, they have provided a sample dataset of a cohort of users.

Uber_Driver_Prediction_Challenge

This notebook is dedicated to the solution of Uber take home challenge. This challenge consists of three main questions and several sub-questions

uberpy

Code to gather data from Uber's API

Uber-DS-Challenge

Uber provided Data Science take home

predictions_bot

Telegram bot that uses genotick for predictions

clearml

ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution

pytorch-sentiment-analysis

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

DataScienceSpecialization.github.io

http://DataScienceSpecialization.github.io

nlp_overview

Overview of Modern Deep Learning Techniques Applied to Natural Language Processing

transformers

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

projector_course

Coding-Playground

jump-orderbook

Coding exercise I did ages ago for a Jump Trading interview

developer-roadmap

Interactive roadmaps, guides and other educational content to help developers grow in their careers.

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.

yake

Single-document unsupervised keyword extraction

TorchScriptTutorial

TorchScript tutorial (python, C++)

sumy

Module for automatic summarization of text documents and HTML pages.

awesome-text-summarization

A curated list of resources dedicated to text summarization

keras-text-summarization

Text summarization using seq2seq in Keras

How-to-Deploy-a-Tensorflow-Model-in-Production

This is the code for the "How to Deploy a Tensorflow Model in Production" by Siraj Raval on YouTube

awesome-production-machine-learning

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

The-Elements-of-Statistical-Learning-Python-Notebooks

A series of Python Jupyter notebooks that help you better understand "The Elements of Statistical Learning" book

mlcourse.ai

Open Machine Learning Course

ebonite

machine learning lifecycle framework

cpp-tutor

Code examples for tutoring modern C++

cpp-copy-elision

labs

This is a collection of tutorials for learning how to use Docker with various tools. Contributions welcome.

awesome-nlp

:book: A curated list of resources dedicated to Natural Language Processing (NLP)

mxnet

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more