I recently completed the Course Supervised Machine Learning: Regression and Classification. I have this question from all experienced individuals, apart from starting the new course, what other things I should do after learning Supervised Machine Learning concepts? (In terms of practice, relevant experience, or projects)
I have heard of Kaggle, but I want wholesome advice on steps that anyone should take as a beginner with the goal of getting a job in this industry!!
PS. I liked the Supervised Learning course, But I am afraid I will forget the concepts if I start another course which is Advanced Learning Algorithms. So any advice around that?
I would say the best thing to do in regards to getting a job would be to think of your own project and tackle it. My reasoning:
- It is a heck of a lot harder to procure you own data from the untamed wilds of the internet
- There is a good chance nobody has used whatever data you scrape, so whatever analysis you do on it is guaranteed to be your original ideas and not some tutorial you copied
- It shows that you are motivated, dedicated and interested enough to do all that work on your own
- You can incorporate more aspects of programming into your final result eg. deployment/production
That said, I also think doing Kaggle’s are a great idea as well, particularly the competitions that have no monetary prize. Kaggle is a great platform for learning data science IMO because the community there is all about sharing information. Even in competitions with a prize of 100K the forums are full of people sharing advice, information and code. Most of the monetary ones are image/video based which sort of require knowledge of neural networks which it doesn’t sound like you have learned yet which is why I recommended the other ones.
Another thing you can work on are leetcodes. I haven’t experienced it, but apparently a lot of tech companies like to ask questions from here. It is also just a good idea to keep your skills sharp.