What you get:
10 ideas for machine learning projects.
Free datasets to use for your projects.
Examples of libraries and algorithms for each case.
Neil and I discussed a different perspective on learning AI.
Many people trying to switch their careers from Software Engineer or other areas to Data Scientist are struggling because they start reading books, doing courses, or spending a lot of money on Master programs, but then they can't land a job. Why?
My observation is that the majority of is that these books, courses, and programs teach the AI used 20 years ago.
This is great if you want to study the history of AI, but not if you want to work in applied AI. Instead of learning the AI that was used 20 years ago, consider learning the AI that is applicable today.
The key to overcoming this issue is, in my opinion, to practice reverse learning: instead of starting from the basic algorithms and going to what is used today, reverse the path, start from the modern techniques, and go back to the basics. This will boost your learning rate 10x.