Surya-Murali/IMDB-Data-Analysis-Using-Spark

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Created over 6 years ago
Updated over 6 years ago

Surya-Murali/IMDB-Data-Analysis-Using-Spark

Surya-Murali

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Data Analysis of IMDB data using Spark. Movie recommendations are made to users based on the other movies that the user has watched.

Real-Time-Object-Detection-With-OpenCV

This project aims to do real-time object detection through a laptop cam using OpenCV. The idea is to loop over each frame of the video stream, detect objects, and bound each detection in a box.

Web-Scraping-and-Amazon-Reviews-Analysis

A Web Scraping project to analyze product reviews in Amazon.com. A sentiment analysis is done and the reviews are sorted and highlighted in green or red based on the sentiment score.

Email-Spam-Classifier-Using-Naive-Bayes

A Naive Bayes spam/ham classifier based on Bayes' Theorem. A bunch of emails is first used to train the classifier and then a previously unseen record is fed to predict the output.

Sentiment-Analysis-of-Twitter-Data-by-Lexicon-Approach

This project uses Lexicon-based approach for sentimental analysis of 1000 recent tweets of 4 countries. A sentiment score for each tweet is computed to ascertain the overall nature of the tweet.

Human-Resource-Analytics-in-R

A Human Resource Analytics project that addresses the question "Why do employees leave?". Also helps us better understand factors for employee satisfaction

Python-Practice

Some Python practice in the form of Jupyter Notebooks and .py files

Jupyter Notebook

PySpark-and-Pandas

Clustering-Using-KMeans

This project uses K-means algorithm to partition a set of points into K clusters. The algorithm works iteratively to assign each data point to one of K groups based on the features provided.

Maps-Weather-Distance-Calculator

An XML project in C# to calculate the distance between people by getting their latitude and longitude positions using Google web services (SOAP & REST).

Patient-Classification-Using-Support-Vector-Machines

Predicting whether a patient is normal or abnormal using SVM. Linear and RBF kernels are used to build the classifier model. Different 'C' and 'gamma' values are chosen to tune the model.

Deep-Learning-With-PyTorch

Deep-Learning-With-PyTorch

Jupyter Notebook

Twitter-Data-Scrapping-and-Wordclouds-of-a-Trending-Topic

A Twitter data mining project to quickly get an overall idea about the tweets of a trending topic. The findings are represented in the form of Wordclouds and dendrograms.