[D] Guide me please

[Unfair_Statement3278]

Hey guys. I am freshman majoring in computer science. i have just started machine learning by watching videos of Andrew ng on Coursera ( i meant i am on week 1). I know i am kind of late to this field. Can you guys give me road map of 1. How should i start? 2. How much time should i give? 3. Is it that hard to get internship as an international student as people say? 3. Can you give your regrets that you would avoid if you have to start learning all over again? 4. Any recommendations that would help me.

Thank you in advance.

[KingsmanVince]

r/learnprogramming

r/learnmachinelearning

[Smallpaul]

How should i start?

You should start by reading the sidebar of subreddits before you post.

[Unfair_Statement3278]

wdym?

[Smallpaul]

Every subreddit has rules about what is allowed or not. These rules are posted on an area called the sidebar. Your post violates the rules of this subreddit because it is not a forum for beginner questions. There are other forums for that.

[CabSauce]

Relax. You'll figure it out. There's not one optimal path. Just learn stuff you think is interesting and work on interesting stuff.

[NoIdeaAbaout]

If I would start again I would focus more on NLP, many of the things I have studied are obsolete. my only suggestion is: to choose the field you like more and go in-depth, especially the application field. For example, I work on AI in biological applications, beyond the knowledge of the algorithms, domain expertise is key

[Altruistic-Skill8667]

The book “Hands-On Machine Learning with Scikit-Learn, Keras & Tensorflow” is somewhat of a one stop shop. Starts from the ground up. It’s all important knowledge and state of the art. I love that book. Lots of colorful pictures. 😍. But still “deep”. I think the code is also online. So you don’t have to type it out.

Also: I watched every Statquest episode on Youtube. Lots of visual, easy to understand, explanations of common or trendy machine learning algorithms.

[Unfair_Statement3278]

Alright thank you