The aim of this training program is to give you a direction and how to use all the resources which are available for free online. In this module we have tried to create some data which is from different places (we tried to get best resources which are already available and also created ours which was not availabe anywhere in the form we wanted) and is curated in a form which will make you aware about your course.
Main aim of this training program is to provide you a path you have to work on, and following are the topics for this module. You can use other resources as well to understan the topics which you can easily find by searching on google. There wiil be a competetion either on Hackerrank or Kaggle on the weelend. And last project you'll have to submit fo which form will be shared on Slack Workspace.
- Part1: Introduction to Machine Learning 📓
- video1: Introduction to Machine Learning 📹
- video2: Introduction to Machine Learning 📹
- Part1: Approching ML problems 📓
- Video: Approching ML problems 📹
- Starting with Anaconda 3📹
- Part2: Numpy📓
- Video1: Numpy📹
- Video2: Numpy📹
- Part2: Numpy Notebook💻
- Part3: Pandas📓
- Video: Pandas📹
- Part3: Pandas Notebook💻
- Part4:Feature Scaling📓
- Part4:Feature Scaling Notebook💻
- Part4:Preprocessing📓
- Video1:Preprocessing 📹
- Video2:Preprocessing📹
- Part5: Data Visualization 📓
- Part5: Visualization Notebook💻
- Part6: Assignment📓
- Part9: Quizz
compulsory for completion(link will be shared on Slack on Monday)