Avinash Bamboria

Projects:

Credit_Ratings

https://github.com/avinashjain314/Credit_Rating

As a part of the machine learning coursework, I worked on a project that involved predicting credit ratings of individuals based on their financial history .Here I pre-processed a dataset containing demographic and financial information of individuals along with their credit rating. I then trained and tested various classification algorithms such as logistic regression, decision tree, and random forest to predict credit ratings of individuals.

Customer Churn

Customer churn is a classic supervised learning technique for classification using feature selection, feature engineering, and various classification machine learning algorithms such as logistic regression, decision tree, random forest, etc. Applied appropriate data science techniques to solve business problems.

Unsupervised Learning

In this project, I utilized the "College.csv" dataset to cluster colleges based on similarities. I employed PCA for feature extraction, followed by K-means algorithm for clustering. The optimal number of clusters was determined using the elbow method or silhouette score. Additionally, I used agglomerative clustering and dendogram to validate the clustering solution. The results were visualized using scatter plots, enabling clear interpretation of the college clusters.

Nba_finals https://github.com/avinashjain314/Nba/blob/master/nba.ipynbIn my NBA Finals project, I utilized label encoding, decision trees, and random forest to analyze and predict outcomes by encoding categorical variables, I transformed them into numerical representations with decision trees, I built a predictive model based on historical data, learning patterns, and relationships,The random forest approach combined multiple decision trees, improving accuracy and mitigating overfitting, These techniques helped me gain insights, make predictions, and understand influential factors in NBA Finals outcomes

I have tried to prepare for UPSC Civil Services, and parallely Taught Maths and Social Science in a Higher Secondary School at my hometown.

• Worked upon DotNet Framework
• Participated in team-based project work, demonstrating ability to fill multiple roles.
• Tackled development tasks based on system requirements and documented approaches.