Jun 2021 – Jul 2021 · 1 mo · Patna, Bihar, India

• Project: Data-Driven Prediction of Battery Cycle Life
• => Led a project focused on accurately predicting the cycle life of batteries before experiencing capacity degradation.
• => Analyzed measurements obtained during a limited number of charging cycles to ascertain battery health and predict its remaining lifespan.
• => Developed a methodology to efficiently estimate the number of cycles a battery has undergone and forecast its potential lifespan before reaching a critical state.
• => Machine Learning algorithms including K-Nearest Neighbors (KNN), Naïve Bayes, Logistic Regression, Support Vector Machine (SVM), Decision Tree, and Random Forest.
• => Achieved an exceptional accuracy rate of 97%, showcasing the effectiveness of the chosen methodology and algorithms
• => Demonstrated the ability to provide accurate cycle life predictions for batteries, enabling proactive maintenance and resource allocation.

Oct 2020 – Oct 2020 · 0 mo

• => Implemented a Decision Tree Classifier on the well-known IRIS dataset for multi-class classification.
• => Visualized the decision tree graphically to gain insights into the classification process and improve interpretability.
• => Demonstrated the ability to make accurate predictions for new data points based on the trained model.
• => Utilized Supervised Machine Learning techniques to predict the percentage of marks for a student based on the number of study hours.
• => Developed a Linear Regression model to establish the relationship between study hours and academic performance.
• => Achieved accurate predictions, enabling informed decision-making for educational support and resource allocation.