Your next steps

[kexej28769@nongnue]

Start listening to OCDevel's Machine Learning Guide Podcast (skip episodes 1, 3, 16, 21, and 26) in your car, while exercising, and/or using your hands and eyes for other activities.
Kaggle's Machine Learning Track Part 1 ں ۔
2. Ready to commit (estimated 80 hours)
By this time, learners will understand their level of interest. Continue with content focused on applying relevant information as soon as possible.


Get Hands-On Machine Learning with bahamas number data -Learn and TensorFlow : Concepts, Tools, and Techniques for Building Intelligent Systems , and read the first two chapters right away. Then use it as a supplement to the Fast.ai course.
3. Broadening your horizons (estimated 115 hours)

Start watching videos and میں شرکتUdacity's Intro to Machine Learning (by Sebastian Thrun and Katie Malone).
اینڈریو

By this point, you will already have AWS running instances, a mathematical foundation, and a broad view of machine learning. This is your jumping off point to determine what you want to do.

You should be able to determine your next step based on your int

Why am I recommending these steps and resources?
I am not qualified to write an essay on machine learning. I do not have a PhD. I took a statistics class in college, which marked the first moment I truly understood the “fight or flight” response. And to top it off, my coding skills are minimal (at best, they are pieces of code reverse-engineered from Stack Overflow). Despite my many shortcomings, this piece was written by an average person like me.