I enjoy doing cool stuff together: mathematics, coding and research.
Experience in Cloud, Distributed computing and Machine Learning
I worked for Praxair as Data Scientist Intern. At Praxair, I delivered a Machine Learning tool for Knowledge management team to automate auditing of Patent documents& Scientific documents. I developed Machine Learning Algorithms for patent group classification, Entity extraction and document classification. I finished my Masters in Data Science from University at Buffalo. I studied Machine Learning, Statistical Data Mining, Programming in Python, Big data and Databases. I worked on a wide range of problems during my masters which include New York city collision Geo spatial analysis, building predictive models for anomaly detection and built ml algorithms from scratch using the math and optimizations.
AWS:Lambda, SageMaker, Redshift, RDS, EMR, EC2, NLP, Deep Learning, Docker
Programming Languages: Python, R, SQL, Shell, Java, JavaScript, MATLAB, HTML/CSS
Packages:scikit-learn, TensorFlow, Keras, Matplotlib, requests, bs4, NumPy, Pandas
Databases& Big data: Oracle, MySQL, NoSQL, Hadoop, MapReduce, Hive, Spark
ML: Regression, Neural Networks, Random Forest, SVM, PCA, Clustering
All of my projects and source code can be found on: github repositories.
The detailed reports, results, code and visualizations can be accessed at: github.com/saikrishna-kanneti