shubhampachori12110095 Goto Github PK
Name: Shubham Pachori
Type: User
Bio: Learning to extract signal from noise.
Location: Somewhere in India
Name: Shubham Pachori
Type: User
Bio: Learning to extract signal from noise.
Location: Somewhere in India
RiVal recommender system evaluation toolkit
Pytorch easy-to-follow step-by-step Deep Q Learning tutorial with clean readable code.
🤖 Chatbot trained by deep reinforcement learning
Colab notebooks part of the documentation of Stable Baselines reinforcement learning library
Source code for the paper <Joint Control of Manufacturing and Onsite Microgrid System via Novel Neural-Network Integrated Reinforcement Learning Algorithms>
The purpose of our research is to study reinforcement learning approaches to building a movie recommender system. We formulate the problem of interactive recommendation as a contextual multi-armed bandit.
Multi-shot Pedestrian Re-identification via Sequential Decision Making (CVPR2018)
Attempting to replicate "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem" https://arxiv.org/abs/1706.10059 (and an openai gym environment)
Reinforcement Learning for Solving the Vehicle Routing Problem
Deep Reinforcement Learning for the JVM (Deep-Q, A3C)
Reinforcement learning for natural language processing reading group
Reinforcement learning A3C LSTM Atari with Pytorch
Companion code to TRC paper: Daniel A. Lazar, Erdem Bıyık, Dorsa Sadigh, Ramtin Pedarsani. "Learning how to Dynamically Route Autonomous Vehicles on Shared Roads". Transportation Research Part C: Emerging Technologies, , vol. 130, pp. 103258, 2021; doi: 10.1016/j.trc.2021.103258.
An environment to high-frequency trading agents under reinforcement learning
Deep Reinforcement Learning for Multiobjective Optimization. Code for this paper
Real-Time Bidding by Reinforcement Learning in Display Advertising
Multiple Reinforcement learning techniques on 3x3 TicTacToe
Reinforcement learning environments for Torch7
Collection of reinforcement learning algorithms
rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compatible with OpenAI Gym.
An implementation of the RL-NTM from http://arxiv.org/abs/1505.00521
Deep Reinforcement Learning For Sequence to Sequence Models
Vehicle Routing Problem with Reinforcement Learning
RMDL: Random Multimodel Deep Learning for Classification
RNF framework for NGS: simulation of reads, evaluation of mappers, conversion of RNF-compliant data.
两层attention 的lstm评论情感分析
tensorflow 实现RNN+Attention文本分类
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.