HR Analytics: Job Change of Data Scientists

The deployed web-app is live now - HR Analytics Web-App Developed a Web-app, which predicts whether an applicant is looking for a new data science job or not with an Accuracy of 84.0%. Preprocessed the data to a specific data form which is suitable for machine learning models to learn. Performed Exploratory Data Analysis to visualize, summarize and interpret the hidden information in the dataset. Applied Dummy Encoding to all Categorical Features.

October 23, 2020

Flight Price Prediction App

The deployed web-app is live now - Give Web-App a Try Developed an app that forecasts flight ticket prices with 94.88 % accuracy Preprocessed the data to a specific data form which is suitable for machine learning model Applied Dummy Encoding to Categorical Features such as Airline, Source and Destination Generated Feature Importance using Random Forest Algorithm Built a web-app using Streamlit and deployed it to the Heroku: A Cloud Application Platform – Feature Importance Plot – Prediction vs Actual Link to Dataset

October 7, 2020

Digit Recognizer

Developed a Convolutional Neural Network to Classify Handwritten Digits with an accuracy of 99.12% Engineered the training, validation (15% of training set) and test datasets into 28 x 28 x 1 pixels Performed pixel normalization to make the model learn better (from [0,255] to [0,1]) Generated Sequential Model with 3 Convolutional Blocks, each block consists of 2 Conv2D layers with LeakyRelU activation layers, then the MaxPool2D layer (to reduce the size of the image), and finally the Dropout layer (to drop the few activation nodes while training).