a.) Using Machine Learning to predict CO2 emissions from a Vehicle by using a dataset provided. It involves using LinearRegression Algorithm to do so.
- Uploading Data And Filtering it(Correcting DataTypes,Nan Values etc if present)
- Normalizing our data
- Distributing data into Training And Testing Set.
- Training Our Model.
- Using it to test/predict data.
- Using variance score to test the efficiency of our model
Also, after using polynomial regression via pipelines we get a score R^2 score of 0.91 which is much better than what we got from our Linear Regression Model
b.)Using Machine Learning to predict stability of a star system based on a few parameters. 1.Using LogisticRegression function in scikit-learn(But because there was no attribute to vary alpha i choose 3.svm classifier to vary c and minimize the error) . 2.Developing logistic regression alogorithm on my own . 3.Using SVM Classifier and varying the values of c and max_iter the mis-classification error(=0.05931) was minimized for c=25.0 and max_iter=2500.0