As part of completion of Machine Learning track, students are suggested to do one complete hands-on project. This course provides 4 problems, out of which, one can be selected for implementation, preferably in python, scikit-learn and matplotlib. Given ppt template needs to be filled with answers got from running the python program.
Students must submit their projects to the following email address: [email protected] within a month from enrollment date.
What am I going to get from this course?
Implement real-life machine learning workflows including data acquisition, preparation, modeling and visualization.
Prerequisites and Target Audience
What will students need to know or do before starting this course?
Machine Learning algorithms like Regression and Classification. Python and associated libraries such as Numpy, Scikit-Learn and Matplotlib.
Who should take this course? Who should not?
Students, as part of completion of Data Science and Machine Learning tracks. Others, familiar with Machine Learning can also benefit from this course.
Module 1: Capstone Project
Idea and the process of Capstone project
Datasets and problem definitions are presented. One of them needs to be chosen for solution.
Slides here are to be filled in with the answers you will get after running your solution. Each slides has questions, which need to be filled in, in the same slide. You will need to send the project to the following email address [email protected]