During my Internship as a Machine Learning in Data Science with SKOLAR, I got to work on Minor as well as Major Assignments as part of my training and work experience. Here are the details on the projects that I chose to work on:-

1. Data Preprocessing pipeline On this project, I used techniques mean imputation, median imputation and KNN imputation on a dataset that had missing values.
2. Lasso Regression Worked on using Lasso Regression to enhance my model on its feature selection capabilities.

1. KNN K values I experimented with differennt values of K to check and see how it affects the model's accuracy and it's flactuation on my model using the KNN classifier.
2. Decision Tree vs Random Forest Classifier I worked two different models using the Decision Tree and Random Forest Classifier algorithm on a dataset and saw how it difered from each other, the advantages and disadvantages of both.
3. PCA Reduction and Re-constructoion Uing PCA, I saw how it was used to reduce the dimension of a large set of data and how it was used to re-construct the data with minimal loss.