Enthusiastic Data scientist and Android developer with hands-on experience.
Machine Learning, Neural Networks, Python,
Android development, Java, Hadoop, Spark,
1- Unsupervised Domain Adaptation of Images - ML
Unsupervised domain adaptation on digit's images by Triplet Loss Network, CNN.
2- Human activity recognition - Machine Learning
HAR system using different classifiers i-e: Logistic Regression, Support Vector Machine (SVM) and Stochastic gradient descent.
3- Traffic Sign Recognition - Machine Learning
A traffic sign recognition system using a Random Forest Classifier which takes a traffic sign image with a small context around it and classifies it.
4- Sentiment Analysis - Spark
The data is prepossessed by applying tokenization, count-vectorizer and
HashingTF and then passed to our machined learning models for final classification.
He not only uses some Libraries. He knows all the science and mathematics that goes behind data science, Machine Learning, and Big Data. I am myself a scientist and mathematician so I can vouch for him.
He is confident, absolutely spot on, and delivers best.
Moreover, he is not made out of Coursera and online courses, he has strong educational background in Machine Learning, and Data Science.
Absolutely Elegant !!
Wish him all the best for future endeavors