Himanshu Ghadigaonkar

When doing Mtech in Artificial Intelligence I have completed following courses: <br/>1. Introduction to AI <br/>2. Machine Learning <br/>3. Statistical Learning <br/>4. Computer Vision <br/>5. Deep Learning <br/>6. Advanced Statistical Learning <br/>7. Robotics and Automation <br/>8. Natural Language Processing <br/>9. Speech Recognition <br/>I have performed well in all the above courses with a cumulative GPA of 3.1. <br/>I would like to teach a student who wants to learn Data science from the basics, from its Mathematical Roots, and then we can move towards, Bigger concepts of Machine Learning, Computer Vision, and Deep Learning. <br/>It is not necessary for you to have a best Mathematics Background, but 30% of 10th class and 50% of 12th class mathematics is necessary for a person. <br/>I will also be revising the same topics like Mean Mode Median, T-test, F-test, Chi-square Test, <br/>Then move to Annova, Mannova. <br/>Then I will cover concepts of Machine Learning like: <br/>Data Preprocessing <br/>Linear Regression, <br/>Logistic Regression, <br/>Decision Trees, <br/>Random Forests, <br/>K nearest Neighbours, <br/>Support Vector Machines (SVMs) <br/>K Means Clustering and Hierarchal Clustering <br/>Artificial Neural Network (ANN) <br/>Convolution Neural Network (CNN) <br/>and some Dimensionality Reduction Techniques too. <br/>We will also learn to use some automated ways of creating Neural Networks, and Google Colab.