I got started with Machine Learning right after Engineering and I quickly fell in love with it. I maintain a blog where I document some of my thoughts and learnings
In my role as a Machine Learning Engineer, I have helped build everything from chatbots to object detection models for 360 degree panaromic images.
I love doing cool and challenging projects in my spare time, latest of which was an end to end project where I try and predict which fighter is gonna win in a UFC (Mixed Martial Arts) fight. It is now an interactive web app and [you can try it out here] (https://ufc-predictions.rajeevwarrier.com). I scraped the data and created the dataset myself.
Predicting who will win a UFC match based on cleaned, preprocessed and feature engineered data scraped from ufcstats.comRead Me
Image classification of the most popular handguns using Transfer Learning (with Resnet-34) based on images scraped from google images.Read Me
Fashion MNISTified image classification using CNNs with Resblock/denseblocks, Batch normalization, weight decay and dropout in pytorchRead Me
How skip connections revolutionized deep learning and allowed deep neural networks (Highway networks, Resnets, Densenets) to cross the 100 layer depth.Read Me
This is the seventh lesson of the series and it covers intuition and implementation details of CNNs, U-nets, GANs, Feature losses and RNNs.Read Me
Gradient Descent is the Algorithm behind the Algorithm. Batch Gradient Descent is probably the most popular of all optimization algorithms.Read Me