Zhao's repositories

Spelling-Correction

Implementing Levenstein distance to do spelling correction

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caffe-tensorflow

Caffe models in TensorFlow

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models

Models built with TensorFlow

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research

comma.ai for the people to experiment with

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TensorFlow-Examples

TensorFlow Tutorial and Examples for beginners

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AlphaGo

A replication of DeepMind's 2016 Nature publication, "Mastering the game of Go with deep neural networks and tree search," details of which can be found on their website.

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awesome-rl

Reinforcement learning resources curated

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caffe

Caffe: a fast open framework for deep learning.

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cs231n.github.io

Public facing notes page

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deep-reinforcement-learning-papers

A list of papers and resources dedicated to deep reinforcement learning

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DetectionTricks

ImageNet Detection Tricks

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fast-rcnn

Fast R-CNN

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JPG-PNG-to-MNIST-NN-Format

Python/Bash scripts for creating custom Neural Net Training Data -- this repo is for the MNIST format

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neural-networks-and-deep-learning

Code samples for my book "Neural Networks and Deep Learning"

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NLP-Spelling-Corrector

Designed a Spelling Corrector using Stupid Backoff, interpolated Kneser-Ney, Good-Turing and Laplace N-gram language modelling

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openpilot

open source driving agent

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py-faster-rcnn

Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version

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pytorch-image-models

PyTorch image models, scripts, pretrained weights -- (SE)ResNet/ResNeXT, DPN, EfficientNet, MixNet, MobileNet-V3/V2/V1, MNASNet, Single-Path NAS, FBNet, and more

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Qix

Node.Js、Golang、Machine Learning、PostgreSQL、Deep Learning

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rcnn

R-CNN: Regions with Convolutional Neural Network Features

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reinforcement-learning

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

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RPN2T

Robust Tracking Using Region Proposal Networks

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tensorflow-resnet

ResNet model in TensorFlow

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try

an example to learn to use git

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wide_resnets_keras

Keras implementation + pretrained weights for "Wide Residual Networks"

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