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analysing-the-affect-of-covid-19-on-stock-prices-of-6-major-banks

This is an analysis of the LIVE stock prices (as on 12/06/2020) of how COVID-19 impacted the stock prices. We try to find out the banks with the biggest losses and analyse which banks would be the riskiest to invest in

analyzing-the-hottest-topics-in-ml-using-lda

Using LDA, we analyze a large collection of NIPS research papers from the past 3 decades, o discover the latest trends in machine learning.

aws-serverless-chatbot

An AWS Lex based serverless chatbot to assist you in Booking a Trip. We combines AWS services like Lex, Polly, Lambda, Dynamo DB and Cloudwatch Logs to give you a wholesome experience of booking a hotel and car for your trip!

classifying-sms-into-spam-and-ham-using-nlp

We do a text analysis using NLP to classify whether a text SMS is spam or ham

comparing-4-unsupervised-classification-techniques-to-predict-loan-deferral-for-a-customer

We compare prediction accuracy of loan deferral for a particular customer using 4 different unsupervised classification techniques

content-recommendation-using-similarity-metrics

We explore 2 methodologies of designing a recommendation system- Content based and using Collaborative Filtering

how-does-super-bowl-outcomes-affect-tv-viewership-and-halftime-performances-

In this project, we find out how TV viewership, half-time performers/musicians interact with Super Bowl scores and outcomes and analyse the trends with time.

lobbyists_4_good-tweet_and_user_analysis

We analyze tweets of Congressmen, to analyse the interest and sentiment for the cause of Lobbyists4Good

perform-ab-testing-to-determine-the-best-version-of-an-e-commerce-website

Using SQL we analyze the AB Test results to determine which test has the best effectiveness based on customer views and order response

pranavtumkur

predicting-cancer-using-support-vector-machines

We use SVM (Support Vector Machines) to build and train a model using human cell records, and classify cells to whether the samples are benign or malignant.

predicting-co2-emission-using-ml-regression-models

Experimenting with various regression models, we try to arrive at the most accurate prediction of the CO2 emission of a new car model

predicting-credit-card-approvals-using-ml

We try to model and train an automatic credit card approval predictor using machine learning techniques, just like the real banks do!

predicting-house-prices-using-deep-learning

In this project, we perform EDA, for the ETL of pricing data of houses in King County, WA to train and implement Deep Learning with an Artificial Neural Network, in order to predict price of a new property on the market

predicting-if-you-would-survive-on-the-titanic

Ever wondered what would happen if you were onboard the Titanic? Would you survive or would you die? This project serves to answer this- We use the Kaggle Titanic dataset to build an ML model in Python. We then use a Flask API to deploy the model to Heroku app; where you can simply answer 7 questions and find out whether you survive or DIE!

predicting-loan-deferral-with-ann-hyperparamater-optimization-and-oversampling

In this project, we build and train a model to predict if a customer will defer on a particular loan on an imbalanced dataset. We'll build a layered ANN for this and try to make our model better using Hyperparamater Optimization, before exploring Oversampling to make it more accurate.

profitability-analysis-using-monte-carlo-simulation

Using VBA Macros, we will determine if setting up a business would be profitable 15 years down the line, subject to 9 inputs, each associated with a certain uncertainty (pun intended!) using Monte Carlo simulation.

similar-movies-suggestions-using-rotten-tomatoes-and-omdb-api

We use 2 APIs, from OMDb (Open Movie Database) and Rotten Tomatoes, to suggest the user, similar movies according to his taste and sort them using the Rotten Tomatoes rating