What's the name of the online course you're taking?
- Complete Machine Learning and Data Science: Zero to Mastery
Complete Machine Learning and Data Science Bootcamp 
✓ Become a Data Scientist and get hired ✓ Deep Learning, Transfer Learning and Neural Networks using the latest Tensorflow 2.0 ✓ Present Data Science projects to management and stakeholders ✓ Real life case studies and projects to understand how things are done in the real world ✓ Implement Machine
What can you reasonably accomplish by the end of this project cycle?
- Start on "setting up your data sci environment" and reaching up to half of Matplot lib section
Tier 1: Share notes of everything I'm learning in Python 2 and how they work Tier 2: Add Repl exercises to the GitHub link to add more depth Tier 3: Create a personality prediction model to take it a step further and apply it in a project setting
What will you create as a demonstration of your progress?
- I can link the Data Structure exercises and links to the repls along with the GitHub repo in which I'm taking notes
What do you wish to get out of taking this course?
- Mastering ML and using it as a tool to create cool automations
Embed your Work Product Here 👇🏽
Notes on Daniel Bourke + Andrei Neagoi's ML Course. Computers were brought into this world to make completing tasks more efficient for humans. The goal of machine learning is to make computers act more and more like humans. The more they act like humans, the more helpful they are for humans!
I wounded up making enough progress to finish setting up DS environment, panda analysis, and numpy. I started on Matplot lib and will next move on to sci kit learn. Here's my GitHub repository with the updated exercises / code that's been written. https://github.com/SnigdhaRoy/ZTM-ML-Notes