Chinthoju Sathvika

Recent graduate in Computer Science with a track record of consistently delivering A+ results through strong analytical, communication, and teamwork skills. Adapts quickly to new environments and approaches every challenge with a positive attitude and a commitment to continuous learning and growth. Possesses a strong organizational skill set, demonstrating a hardworking and passionate approach to securing an entry-level position.

1. Mini Project : Hybrid Machine Learning Classification Technique for Improving the Accuracy of Heart Disease

The Proposed work investigates four different Algorithms such as the Hidden Markov Model (HMM), Support Vector Machine(SVM), Artificial Neural Network ( ANN), and a form of Decision Tree (J48). The Proposed method robustly analyzes these four methods to exploited statistics and Opts for the pair of the finest algorithm that utilizes a linear model based on the feature selection process

2. Major Project : Machine Learning Based Predicative Mechanism For Internet Bandwidth

In this paper, we proposed a machine learning based prediction approach for a future bandwidth prediction . We visualized the result of prediction using different graphs . We can conclude that random forest algorithm gives better performance in terms of accuracy . Random forest algorithm provides approximately 82% accuracy , which is better than other algorithms. This contribution can uphold situation where limited bandwidth needs to be predicted.