Machine learning and data analytics

Question

I'm super interested with machine learning and data analytics. I've invested time in learning python and Js how can I start the journey for machine learning and data analytics/science? Clear insights would be appreciated.

Answer 1

Some basic knowledge in statistics is absolutely necessary. If you have that, you should probably start with some course, maybe you find a good one on YouTube, if you are not at a university.

Don't waste too much time on the mathematical groundwork (with that I mean convergence proofs and what not), it is probably not worth your time, as the results are weak and methods used a little more involved.

When it comes to implementation, Python with tensorflow is nice to start playing around with.

Answer 2

there are plenty of libraries like sklearn, and YouTube tutorials on machine learning.

Answer 3

Already proficient in JavaScript and Python? Fantastic! Here's how to proceed:
Start by improving your foundational knowledge of mathematics, particularly in the areas of probability, statistics, and linear algebra. These are the foundation of the majority of machine learning algorithms. Next, acquire the necessary Python libraries to work with actual data, such as Pandas, NumPy, Matplotlib, and Scikit-learn.
Start with simple analytics tasks like trend visualisation or value prediction. After gaining confidence, delve into machine learning and investigate supervised and unsupervised models like clustering, decision trees, and regression.
Make practical projects, post them to GitHub, and use blogs or a portfolio to demonstrate what you've learnt. Make use of sites like Kaggle to push yourself and develop.
Join LinkedIn groups and follow communities like Towards Data Science and Analytics Vidhya to stay current.

You will forge a solid career in machine learning and analytics with persistent learning and project development.