Krithick Balaji Ramesh

PROFILE SUMMARY: To enhance my Educational and Professional skills in a stable and dynamic workplace and to establish my career path in an organization that gives me an opportunity for self-improvement & leadership which help me to showcase my talent and attain practical knowledge thereby climbing the career ladder.

PROFESSIONAL SUMMARY: Experienced in python data manipulation for loading and extraction as well as with python libraries such as Numpy, sciPy and Pandas for data analysis and numerical computations. Proficient in machine learning and deep learning skills for multiple applications including Computer Vision, Recommendation Systems and Natural Language Processing Highly skilled in using pandas, Numpy, seaborn, Scipy,mat-plot-lib, sci-kit-learn in python to developing various machine learning algorithms.

Participated and grabbed certification in 6th National Engineering Olympiad in UG

• ROCK vs MINE Prediction Key learning from the project : In this project, I build a system in python programming language that can predict whether an object is either Rock vs Mine with SONAR Data. For this use case, I used Logistic Regression Model for prediction. The focus of this project will be the Sonar Mines vs Rocks datasets. The problem is to predict metal or rock objects from sonar return data.
• SPAM Mail Prediction Key learning from the project : In this project, I build a Spam Mail prediction system using Machine Learning with python. I used Logistic Regression Model for prediction. It check whether
• Gold price prediction using random forest regression Key Learning from the project : In this project, I build Gold price prediction using machine learning with python. For this Prediction, I have used a Random Forest Regress-or in supervised learning algorithm, ensemble learning method for classification and regression.

• Data Structure and Algorithm
• PPS(programming and problem solving)
• Machine learning
• Data Analysis
• OOP(Object Oriented Programming in c++)
• Deep Learning
• Neural Networks

• Face Recognition using machine learning
• Smile detector
• Identifying Object with CNNs(Convolutional Neural Networks)
• Computer Vision (Lane Detection Problem in self Driving cars)
• Viola-Jones Face Detection Algorithm Theory