• Python (Pandas, BeautifulSoup, Scrappy, Numpy, ScikitLearn, Matplotlib, NLTK, Seaborn, Keras)
• R (Readr, ODBC, tibble,tidyr,dplyr,ggplot2,lm, party, RandomForest )
• Machine Learning, Data science, Deep learning
• Statistical Analysis, Data Mining, Data Visualisation, Optimisation Techniques
• Linear/Logistic Regression, SVM, Naives Bayes, PCA, Ensemble Trees, Random
• Implemented discretization and binning, data wrangling: cleaning, transforming, merging and reshaping data frames.
• Understanding the Data and analysing the missing data, Multi-Collinearity, outliers, conversion of categorical attributes into numerical.
• Integrated applications with designing database architecture and server scripting, studying & establishing
• Designed data visualization to present current impact and growth
• Developed Natural Language Processing and Machine Learning Systems
• Maintained customers relationship management databases (MySQL / PostgreSQL)