cmhuang0328
Data Science enthusiasts, Rutgers MS BA and NYU MS CS Passionate about Machine Learning, Data Mining, Databases and Web Development
Jersey City, USA
cmhuang0328's Stars
opendilab/awesome-RLHF
A curated list of reinforcement learning with human feedback resources (continually updated)
cmhuang0328/Deep-Trading
Algorithmic trading with deep learning experiments
cmhuang0328/hotel-database-system
Python scripts to MySQL server, integrated with Apache and CGI, front-end built with HTML5/CSS3
cmhuang0328/IMDB-rating
IMDB movie rating prediction
cmhuang0328/netflix-recommendation-system
Netflix_recommendation_system with Python for data cleaning and visualization, and Hadoop Mapreduce for recommnedtion systems
cmhuang0328/kaggle-renthop
Kaggle Renthop Prediction with Python XGBoost, R
cmhuang0328/discrete-optimization
Rutgers Discrete Optimization Course in AMPL(for custtingstock, backpack, netflow, roadmap)
cmhuang0328/algorithmic-machine-learning
Rutgers Algorithmic Machine Learning Course in R(with regression, classification, neural network)
cmhuang0328/interactive-coding-challenges
Huge update! Interactive Python coding interview challenges (algorithms and data structures). Includes Anki flashcards.
cmhuang0328/Become-A-Full-Stack-Web-Developer
Free resources for learning Full Stack Web Development
cmhuang0328/mongo
The MongoDB Database
cmhuang0328/hadoop
Mirror of Apache Hadoop
cmhuang0328/system-design-interview
System design interview for IT companies
cmhuang0328/redis
Redis is an in-memory database that persists on disk. The data model is key-value, but many different kind of values are supported: Strings, Lists, Sets, Sorted Sets, Hashes, HyperLogLogs, Bitmaps.
cmhuang0328/awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
cmhuang0328/system-design-primer
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
cmhuang0328/intro-data-science
Rutgers Introduction to Data Science Course Including Python Tutorial for peers, and NBA,MLB, Netflix dataset cleaning and visualization