Pinned Repositories
Adult-Income-Prediction
Advanced-Data-Science-Projects
alta
The Art of Literary Text Analysis
Android-Face-Recognition-with-Deep-Learning-Library
Face Recognition library for Android devices is an Android library (module) which includes several face recognition methods.
android-interview-questions
Your Cheat Sheet For Android Interview - Android Interview Questions
Android-Universal-Image-Loader
Powerful and flexible library for loading, caching and displaying images on Android.
android_guides
Extensive Open-Source Guides for Android Developers
http-api-design
HTTP API design guide extracted from work on the Heroku Platform API
Huawei_Honor_Smart_SMS_project-
Music-Mood-Detection-using-Text-Mining-on-Lyrics-
During my undergrad, I implemented a music recommendation system based on music digital track analysis. However, it's time for me to use text mining technology on lyrics to upgrade that project. Goals: (1)build a music mood(happy or sad) classifier based on lyrics analysis (2)what words and their distributions are in different mood categories? (3)How are the key words change in songs for the recent years? Project evaluation: (1)data collection: the training data and validation data will be collected from the largest lyric database on Lyricwiki.org (2)feature selection: the most common feature type to consider are BOW(bag of word) and POS(part of speech) combined with stemming using word-net (3)Training model : SVM, Naive Bayes using grid search method. (4)data visualization for goal two and three This project will be done using python on jupyter notebook. reference: Hu, X. (2010). Improving music mood classification using lyrics, audio and social tags (Doctoral dissertation, University of Arizona).
DarrenKe's Repositories
DarrenKe/Huawei_Honor_Smart_SMS_project-
DarrenKe/Music-Mood-Detection-using-Text-Mining-on-Lyrics-
During my undergrad, I implemented a music recommendation system based on music digital track analysis. However, it's time for me to use text mining technology on lyrics to upgrade that project. Goals: (1)build a music mood(happy or sad) classifier based on lyrics analysis (2)what words and their distributions are in different mood categories? (3)How are the key words change in songs for the recent years? Project evaluation: (1)data collection: the training data and validation data will be collected from the largest lyric database on Lyricwiki.org (2)feature selection: the most common feature type to consider are BOW(bag of word) and POS(part of speech) combined with stemming using word-net (3)Training model : SVM, Naive Bayes using grid search method. (4)data visualization for goal two and three This project will be done using python on jupyter notebook. reference: Hu, X. (2010). Improving music mood classification using lyrics, audio and social tags (Doctoral dissertation, University of Arizona).
DarrenKe/Adult-Income-Prediction
DarrenKe/http-api-design
HTTP API design guide extracted from work on the Heroku Platform API
DarrenKe/Advanced-Data-Science-Projects
DarrenKe/alta
The Art of Literary Text Analysis
DarrenKe/Android-Face-Recognition-with-Deep-Learning-Library
Face Recognition library for Android devices is an Android library (module) which includes several face recognition methods.
DarrenKe/android-interview-questions
Your Cheat Sheet For Android Interview - Android Interview Questions
DarrenKe/Android-Universal-Image-Loader
Powerful and flexible library for loading, caching and displaying images on Android.
DarrenKe/android_guides
Extensive Open-Source Guides for Android Developers
DarrenKe/awesome-tensorflow
TensorFlow - A curated list of dedicated resources http://tensorflow.org
DarrenKe/cs199-sp17
Applied Cloud Computing - University of Illinois, Spring 2017
DarrenKe/ctci
Cracking the Coding Interview, 5th Edition
DarrenKe/darknet
Convolutional Neural Networks
DarrenKe/facenet
Face recognition using Tensorflow
DarrenKe/gaia_data_visualization
Learn some visualization technologies with gaia_data
DarrenKe/info490-fa16
INFO 490: Foundations of Data Science, offered in the Fall 2016 Semester at the University of Illinois
DarrenKe/info490-sp17
Advanced Data Science, University of Illinois Spring 2017
DarrenKe/java-design-patterns
Design patterns implemented in Java
DarrenKe/leetcode
Data structures and algorithms for interview preparation
DarrenKe/Medical-Knowledge-Training-Platform-Android-Client-
DarrenKe/Mining_Frequent_Patterns
Implement Apriori algorithm and closed/maximal pattern mining with Python
DarrenKe/MLAlgorithms
Minimal and clean examples of machine learning algorithms
DarrenKe/opencv
Open Source Computer Vision Library
DarrenKe/pafy
Python library to download YouTube content and retrieve metadata
DarrenKe/project-spring2017
Final project template
DarrenKe/spring2017
Course materials, including syllabus, datasets, scripts, lectures, etc
DarrenKe/test
DarrenKe/Text-Mining-Course
Course Notes for 590TXL, University of Illinois at Urbana-Champaign
DarrenKe/twitter_nlp
Twitter NLP Tools