ncondo

Nicholas Condo's starred repositories

applied-ml

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

MIT27224 949 24

fastai

The fastai deep learning library

Language:Jupyter NotebookApache-2.026188 605 1798

fastbook

The fastai book, published as Jupyter Notebooks

Language:Jupyter NotebookNOASSERTION21675 507 235

awesome-production-machine-learning

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

MIT17427 404 76

The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.

Language:C#NOASSERTION17018 555 2906

deeplearning-models

A collection of various deep learning architectures, models, and tips

Language:Jupyter NotebookMIT16658 593 29

tfjs-models

Pretrained models for TensorFlow.js

Language:TypeScriptApache-2.014035 2760

Cookbook

The Data Engineering Cookbook

Apache-2.013645 537 135

data-engineer-roadmap

Roadmap to becoming a data engineer in 2021

12340 545 63

MLAlgorithms

Minimal and clean examples of machine learning algorithms implementations

Language:PythonMIT10715 424 28

machine-learning-systems-design

A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems"

Language:HTML8982 302 10

data-science-interviews

Data science interview questions and answers

Language:HTMLCC-BY-4.08824 225 16

data-science-from-scratch

code for Data Science From Scratch book

Language:PythonMIT8642 641 84

cookiecutter-data-science

A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.

Language:PythonMIT8244 122 174

Machine-Learning-Collection

A resource for learning about Machine learning & Deep Learning

Language:PythonMIT7533 115 125

Grokking-Deep-Learning

this repository accompanies the book "Grokking Deep Learning"

Language:Jupyter Notebook7405 320 50

course-v3

The 3rd edition of course.fast.ai

Language:Jupyter NotebookApache-2.04899 228 161

120-Data-Science-Interview-Questions

Answers to 120 commonly asked data science interview questions.

3694 128 4

responder

A familiar HTTP Service Framework for Python.

Language:PythonNOASSERTION3593 91 218

YAD2K

YAD2K: Yet Another Darknet 2 Keras

Language:PythonNOASSERTION2714 91 175

decaNLP

The Natural Language Decathlon: A Multitask Challenge for NLP

Language:PythonBSD-3-Clause2343 117 40

github-spray

:octocat: Draw on your GitHub contribution graph ░▒▓█

Language:JavaScriptMIT1346 180

pokerstove

poker evaluation and enumeration software

Language:C++BSD-3-Clause798 83 45

pydfs-lineup-optimizer

Daily Fantasy Sports lineup optimzer for all popular daily fantasy sports sites

Language:PythonMIT419 43 398

dfs_optimizers

Optimizers for Daily Fantasy Sports written in python and based on Picking Winners paper.

Language:PythonMIT63 7 6

SDC-System-Integration

Self Driving Car Engineer Nanodegree System Integration Capstone Project

Language:Jupyter NotebookMIT46 80

Daily-Fantasy-Baseball-Contests-in-DraftKings

This is the code for constructing a portfolio of lineups for DraftKings baseball contests with a top heavy payoff structure. This code is based on the paper Picking Winners Using Integer Programming by David Hunter, Juan Pablo Vielma, and Tauhid Zaman (https://arxiv.org/abs/1604.01455).

Language:Julia37 4 17