These are assignments related to the graduate course, 'Machine Learning' at NYU by Professor Hellerstein
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Updated
May 2, 2018 - Jupyter Notebook
These are assignments related to the graduate course, 'Machine Learning' at NYU by Professor Hellerstein
Machine Learning
Naive Bayes Algorithm Implementation and Use Cases (Gaussain Naive Bayes, Multinomial Naive Bayes)
Implementation of Gaussian and Multinomial Naive Bayes Classifier using Python, Pandas, and NumPy without using any off the shelf library usi
A implementation of Naïve Bayes Machine Learning Algorithm from scratch. Includes implementations for Gaussian Naïve Bayes, Categorical Naïve Bayes, Binary Confusion Matrix, Binary Precision, Recall, F Measure scores
Loan Prediction Using Machine Learning Models
Using Machine Learning to predict which news article belongs to which news group.
Implementing a Gaussian Naive Bayes classifier in Python and R
Classification using Multinomial and Gaussian Naive Bayes
Webapp para classificar comentários (positivos, negativos e neutros) advindos do Facebook usando Natural Language Toolkit (NLTK) + Django e Bootstrap na interface Web.
This is my Data Mining course assignment for Naive Bayes Classification algorithm. I implemented Gaussian Naive Bayes on Python.
Fast explication of Gaussian NB
Fake News Detection
Perturbation based Technique for Privacy Preserving Social Network Data
This project aims to reduce the time delay caused due to the unnecessary back and forth shuttling between the hospital and the pathology lab. Here a machine learning algorithm will be trained to predict a liver disease in patients using a data-set collected from North East of Andhra Pradesh, India.
The Santander Customer Transaction Prediction is a competition for beginners of ML learners.
Implementation of a multi class Gaussian Naive Bayes classifier in python from scratch.
Stacking Classifier with parallel computing architecture based on Message Passing Interface.
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