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Python Backtesting library for trading strategies

A curated list of insanely awesome libraries, packages and resources for systematic trading. Crypto, Stock, Futures, Options, CFDs, FX, and more | 量化交易 | 量化投资

[🔥updating ...] 自动量化交易机器人 Qbot is an AI-oriented quantitative investment platform, which aims to realize the potential, empower AI technologies in quantitative investment. https://ufund-me.github.i…

Easy-to-use,Modular and Extendible package of deep-learning based CTR models .

A deep matching model library for recommendations & advertising. It's easy to train models and to export representation vectors which can be used for ANN search.

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A tool to label bounding box and person attributes in images

ReforcementLearning in Action

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

Deep Learning Tutorial notes and code. See the wiki for more info.

Code base for solving Markov Decision Processes and Reinforcement Learning problems using Recurrent Convolutional Neural Networks.

This repository contains Deep Learning based articles , paper and repositories for Recommender Systems

Recommender Systems using factored MDP

Tensorflow-based Recommendation systems

Python implementation of "Factorizing Personalized Markov Chains for Next-Basket Recommendation"

A set of Deep Reinforcement Learning Agents implemented in Tensorflow.

Recommendation engine based on contextual word embeddings

GRU4Rec is the original Theano implementation of the algorithm in "Session-based Recommendations with Recurrent Neural Networks" paper, published at ICLR 2016 and its follow-up "Recurrent Neural Ne…

Learning to Recommend using a Deep Reinforcement Agent

Bayesian Personalized Ranking for Spark

This the implementation of PMF using Pytorch

This is a dataset which provides movie tags crawlered from the official website for Movielen-1m, Movielen-10m and Movielen-20m.

This is a python code for probabilistic matrix factorization in recommendation.