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zxsted's Projects

matchingnetwork icon matchingnetwork

Implementation of "Matching Networks for One Shot Learning" in Keras https://arxiv.org/abs/1606.04080

matchingnetworks icon matchingnetworks

An attempt at replicating the Matching Networks for One Shot Learning in Tensorflow - Paper URL: https://arxiv.org/pdf/1606.04080.pdf

matchlstm icon matchlstm

implementation match mLstm in TensorFlow 1.0

matchzoo icon matchzoo

MatchingZoom is a toolkit for text matching. It was developed with a focus on enabling fast experimentation.

matthew-irl icon matthew-irl

My version of the github repo https://github.com/MatthewJA/Inverse-Reinforcement-Learning by Matthew

mcmc-sampling icon mcmc-sampling

The theory and implement of Metropolis Hastings Algorithm and Gibbs sampling

mcts icon mcts

An implementation of Monte Carlo Tree Search in python

mcts-1 icon mcts-1

Java implementation of UCT based MCTS and Flat MCTS

mcts-2 icon mcts-2

Python Implementations of Monte Carlo Tree Search

medium icon medium

Code related to blog posts on my Medium page

meirl icon meirl

An Implementation of Maximum Entropy Inverse Reinforcement Learning

mem2seq-1 icon mem2seq-1

Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Oriented Dialog Systems

memnn icon memnn

Theano implementation of Memory Networks

meta-critic-networks icon meta-critic-networks

Pytorch code for Arxiv Paper: Learning to learn: Meta-Critic Networks for Sample-Efficient Learning

meta-rl icon meta-rl

Implementation of Meta-RL A3C algorithm

mini_qa icon mini_qa

Toy question answering program. Aimed at "Who ....?" questions, e.g., "Who invented the C programming language?"

mjhmc icon mjhmc

Python implementation of Markov Jump Hamiltonian Monte Carlo

ml-from-scratch icon 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.

ml-nlp icon ml-nlp

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现,也是作为一个算法工程师必会的理论基础知识。

mlalgorithms icon mlalgorithms

Minimal and clean examples of machine learning algorithms

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