Charles (cszhang)

cszhang

Geek Repo

Location:Redmond, WA

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Charles's starred repositories

Polly

Polly is a .NET resilience and transient-fault-handling library that allows developers to express policies such as Retry, Circuit Breaker, Timeout, Bulkhead Isolation, and Fallback in a fluent and thread-safe manner. From version 6.0.1, Polly targets .NET Standard 1.1 and 2.0+.

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azure-docs

Open source documentation of Microsoft Azure

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system-design-interview

System design interview for IT companies

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fresco

An Android library for managing images and the memory they use.

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CtCI-6th-Edition

Cracking the Coding Interview 6th Ed. Solutions

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guava

Google core libraries for Java

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enzyme

JavaScript Testing utilities for React

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react-devtools

An extension that allows inspection of React component hierarchy in the Chrome and Firefox Developer Tools.

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gensim

Topic Modelling for Humans

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react-slingshot

React + Redux starter kit / boilerplate with Babel, hot reloading, testing, linting and a working example app built in

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react-chartjs-2

React components for Chart.js, the most popular charting library

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react-d3-graph

Interactive and configurable graphs with react and d3 effortlessly

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flask-chatterbot

Simple boilerplate for ChatterBot using Flask

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dynamic-coattention-network-plus

Dynamic Coattention Network Plus (DCN+) TensorFlow implementation. Question answering using Deep NLP.

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ChatLearner

A chatbot implemented in TensorFlow based on the seq2seq model, with certain rules integrated.

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DeepQA

My tensorflow implementation of "A neural conversational model", a Deep learning based chatbot

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ChatterBot

ChatterBot is a machine learning, conversational dialog engine for creating chat bots

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tensorflow

An Open Source Machine Learning Framework for Everyone

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nmt

TensorFlow Neural Machine Translation Tutorial

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kafka-streams-machine-learning-examples

This project contains examples which demonstrate how to deploy analytic models to mission-critical, scalable production environments leveraging Apache Kafka and its Streams API. Models are built with Python, H2O, TensorFlow, Keras, DeepLearning4 and other technologies.

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real-time-deep-face-recognition

using facenet algorithm

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facenet

Face recognition using Tensorflow

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openface

Face recognition with deep neural networks.

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How-to-Predict-Stock-Prices-Easily-Demo

How to Predict Stock Prices Easily - Intro to Deep Learning #7 by Siraj Raval on Youtube

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TextBlob

Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.

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nltk

NLTK Source

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awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

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