Rohan Khameshra's starred repositories
nlp-tutorial
Natural Language Processing Tutorial for Deep Learning Researchers
applied-ml
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
wallstreet
Real time stock and option data.
build-your-own-x
Master programming by recreating your favorite technologies from scratch.
markdown-cheatsheet
Markdown Cheatsheet for Github Readme.md
TensorComprehensions
A domain specific language to express machine learning workloads.
keras-yolo2
Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon run entirely in brower is accessible at https://git.io/vF7vI (not on Windows).
auquan-toolbox-python
Backtesting toolbox for trading strategies - DEPRECATED
finmarketpy
Python library for backtesting trading strategies & analyzing financial markets (formerly pythalesians)
awesome-quant
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
deepImageAestheticsAnalysis
ECCV2016 - fine-grained photo aesthetics rating with interpretability
DeepRLHacks
Hacks for training RL systems from John Schulman's lecture at Deep RL Bootcamp (Aug 2017)
deepbootcamp
Solved lab problems, slides and notes of the Deep Reinforcement Learning bootcamp 2017 held at UCBerkeley
deep-learning-papers
Papers about deep learning ordered by task, date. Current state-of-the-art papers are labelled.