Pinned Repositories
BIOMETRIC-BASED-ATM
choice-APP
Coding-challenge
Coding challenges and its solution
community-detection-in-facebook-BillGates-Profile
Hadoop
Movie-recommendation-system
Recommendation systems # # Here we'll implement a content-based recommendation algorithm. # It will use the list of genres for a movie as the content. # The data come from the MovieLens project: http://grouplens.org/datasets/movielens/ #
Personal-medical-Application
Real-Time-Data-Pipeline-Taxi-Price-Surge
REAL-TIME DATA PIPELINE TO ANALYZE TAXI PRICE SURGE
Sentiment-and-Cluster-analysis-through-twitter
mpradeep1994's Repositories
mpradeep1994/Movie-recommendation-system
Recommendation systems # # Here we'll implement a content-based recommendation algorithm. # It will use the list of genres for a movie as the content. # The data come from the MovieLens project: http://grouplens.org/datasets/movielens/ #
mpradeep1994/choice-APP
mpradeep1994/Real-Time-Data-Pipeline-Taxi-Price-Surge
REAL-TIME DATA PIPELINE TO ANALYZE TAXI PRICE SURGE
mpradeep1994/BIOMETRIC-BASED-ATM
mpradeep1994/Coding-challenge
Coding challenges and its solution
mpradeep1994/community-detection-in-facebook-BillGates-Profile
mpradeep1994/Hadoop
mpradeep1994/Personal-medical-Application
mpradeep1994/Sentiment-and-Cluster-analysis-through-twitter
mpradeep1994/SOA_WEBSERVICE
COMPLETE WEB SERVICE DEMO
mpradeep1994/banking-console
mpradeep1994/chatbot
An AI Based Chatbot
mpradeep1994/data-science-from-scratch
code for Data Science From Scratch book
mpradeep1994/Data-Science-w-Python
mpradeep1994/election-candidate-profile-analysis
Collecting a political social network In this assignment, I've given you a list of Twitter accounts of 4 U.S. presedential candidates. The goal is to use the Twitter API to construct a social network of these accounts.
mpradeep1994/hadoop-book
Example source code accompanying O'Reilly's "Hadoop: The Definitive Guide" by Tom White
mpradeep1994/IMDB-movie-review-prediction-of-user
build a text classifier to determine whether a movie review is expressing positive or negative sentiment. The data come from the website IMDB.com. You'll write code to preprocess the data in different ways (creating different features), then compare the cross-validation accuracy of each approach. Then, you'll compute accuracy on a test set and do some analysis of the errors. The main method takes about 40 seconds for me to run on my laptop. Places to check for inefficiency include the vectorize function and the eval_all_combinations function
mpradeep1994/ISSUE-TRACKING-SYSTEM
mpradeep1994/main
CS579: Online Social Network Analysis at the Illinois Institute of Technology
mpradeep1994/mpradeep1994.github.io
mpradeep1994/portfolio
my portfolio
mpradeep1994/Python
mpradeep1994/slate
Beautiful static documentation for your API
mpradeep1994/TIME_PASS
sample project for simple thoughts
mpradeep1994/uwsgi-nginx-flask-docker
Docker image with uWSGI and Nginx for Flask applications in Python running in a single container. Optionally with Alpine Linux.