I am a Machine Learning Engineer, a MLND graduate, Udacity, have worked on supervised, unsupervised and deep learning problems. Have worked with various libraries such as sklearn, tensorflow, keras, pandas, numpy, opencv, xgboost, lightgbm etc. Also have experience with working on AWS Instance. Ranked among top 6% and 3% on hackerearth machine learning competitions and ranked among top 40% on KKBOX Music Recommendation challenge, Kaggle. Some of the projects that I have worked on include Predict Network Attacks, Predict Fraudulent Transactions, Classify Dog Breeds using Transfer Learning, Classify objects using Cifar-100 and Caltech-101 datasets, Predict House Pricing, Classify customer segments, etc.