nhu2000 Goto Github PK

accent_analysis

adtech-dash

A Scalable Ad Classification Pipeline, REST API, and Visualization, using Apache Spark, Apache Kafka, Apache HBase, Scalatra, Amazon Web Services, Highcharts

advanced-deep-trading

Mostly experiments based on "Advances in financial machine learning" book

agatha

Stock market prediction using Keras

age-gender-estimate-tf

Face age and gender estimate using TensorFlow

airbnbscrape

Python Function To Scrape Airbnb

all-things-data-science

alyn

Detect and fix skew in images containing text

angel

A Flexible and Powerful Parameter Server for large-scale machine learning

arxiv-doc2vec-recommender

Discovers similarity between scientific papers

asx_gym

Open AI Gym Env for Australia Stock Exchange (ASX)

augmentor

Image augmentation library in Python for machine learning.

automatedstocktrading-deepq-learning

Every day, millions of traders around the world are trying to make money by trading stocks. These days, physical traders are also being replaced by automated trading robots. Algorithmic trading market has experienced significant growth rate and large number of firms are using it. I have tried to build a Deep Q-learning reinforcement agent model to do automated stock trading.

automatic_speech_recognition

End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow

autosub

Command-line utility for auto-generating subtitles for any video file

awesome-deep-trading

List of awesome resources for machine learning-based algorithmic trading

awesome-python-cn

Python资源大全中文版，包括：Web框架、网络爬虫、模板引擎、数据库、数据可视化、图片处理等，由伯乐在线持续更新。

barcode-service

Simple Docker microservice that extracts barcodes or QR codes from images.

barcodesdetecting

A script used to compute distance from camera to object using OpenCV and python

benjamin-graham-and-warren-buffett-model-stock-exchange-

There are about 4000 stocks which are actively traded on the stock exchanges at BSE and NSE. Can we extract public financial data from sites like moneycontrol.com to find which are the fundamentally strong stocks. On what stocks would the father of value investing, Benjamin Graham and Warren Buffett the most successful investors in the world make their investments on. Benjamin Graham and Warren Buffett Model Step 1: Filter out all companies with sales less than Rs 250 cr. Companies with sales lower than this are very small companies and might not have the business stability and access to finance that is required for a safe investment. This eliminates the basic business risk. Step 2: Filter out all companies with debt to equity greater than 30%. Companies with low leverage are safer. Step 3: Filter out all companies with interest coverage ratio of less than 4. Companies with high interest coverage ratio have a highly reduced bankruptcy risk. Step 4: Filter out all companies with ROE less than 15% since they are earning less than their cost of capital. High ROE companies have a robust business model, which generates increased earnings for the company typically. Step 5: Filter out all companies with PE ratio greater than 25 since they are too expensive even for a high-quality company. This enables us to pick companies which are relatively cheaper as against their actual value. He points out that applying these filters enables us to reduce and even eliminate a lot of fundamental risks while ensuring a robust business model, strong earning potential and a good buying price.

big-data-soccer-analytics

CS594-BigData-Project

blog

Source code of my blog

blurred-barcode-extraction

building-spark-applications-live-lessons

Supporting content (slides and exercises) for the Addison-Wesley (Pearson) video series covering best practices for developing scalable Spark applications for predictive analytics in the context of a data scientist's standard workflow.

capmarket

capstone-project

capstone_project

Susie X Sun Capstone Project

carl_capstone

chainerrl

ChainerRL is a deep reinforcement learning library built on top of Chainer.

chatbot

一个可以自己进行训练的中文聊天机器人， 根据自己的语料训练出自己想要的聊天机器人，可以用于智能客服、在线问答、智能聊天等场景。