ML enthusiast with 2.5 years of implementation experiences in machine learning and deep learning including regression, classification, neural network, natural language processing(NLP), etc and handling complex problems using transfer-learning techniques over various domains. Overall 4.5+ years programming experience with Python, SQL, PLSQL.
End-to-End Machine Learning expertise
undefinedINTERESTING FACTS about Lok Sabha Election - 2019
https://www.kaggle.com/shivamsharma22/interesting-facts-about-lok-sabha-election-2019
Analyzed the Education Qualification of the Candidates, Number of Candidates with Criminal Background contesting the elections, Most Aged and Young candidates, Number of Female candidates elected, etc.
Netflix Bollywood Movies Analysis
https://www.kaggle.com/shivamsharma22/netflix-bollywood-movies-analysis
Separated out Bollywood movies on the basis of its rating into various categories - Family Movie, Child Movie, Adult Movie, Comedy Movie, etc. Categorized movies on the basis of Individual Actors and Actresses and much more stuff.
Individual IPL Team's Performance over the years
https://www.kaggle.com/shivamsharma22/individual-ipl-team-s-performance-over-the-years
Analyzed Individual IPL Team’s performance, their Good and Bad seasons, their Strong and Weak Opponents and much more.
Africa Crises - Complete Analysis(Accuracy-98.86%)
https://www.kaggle.com/shivamsharma22/africa-crises-complete-analysis-accuracy-98-86
Cleaned up the Data, Dealt with NaN values, Converted Categorical features to Numeric, removed the features which were highly correlated with each other, performed Exploratory Data Analysis and applied various Classifier Models. Gained the highest accuracy of 98.86% by using Random Forest Classifier.