5 best and free Machine learning online course – Hot MIT course

5 best and free Machine learning online course: Are you someone who believes that you need to take some really expensive course in order to learn machine learning. Well, today I’m going to tell you guys how to learn machine learning for free. The internet has tons of free resources out. But today I will be sharing the main five courses which I think are really essential for beginners. And if you don’t want to invest a ton of money.

MIT open learning

MIT open learning has existed for a long time. It has many other courses besides machine learning. It also has some really small machine learning courses but this is the very first time that MIT has released an in-depth machine learning course. It is something which is catered to beginners as well. I definitely recommend that you guys check out the course.

It’s a 13 week-long introductory course to machine learning which covers everything from the basics and it gets deeper into things like neural networks and recurrent neural networks. Definitely check that out

Coursera

It’s really a great site which I highly recommend everyone to check out because it has actual professors from top universities. Teaching you what they are really good at. Coursera has a ton of different machine learning courses but one of the best Andrew young in collaboration with Stanford University. He is really well known in the machine learning community and he’s a great educator as well so definitely check out. I recommend it, especially for beginners.

After completing that you might think about dwelling further maybe even getting a certification. So there’s also another entire track on Coursera, which allows you to apply for the google TensorFlow developer certification. It’s a great opportunity to have that kind of certificate on your portfolio as a machine learning engineer.

kaggle

kaggle is pretty well known in the data science community. especially if you’re a machine learning engineer I feel like there’s a lot to learn there as well. It has so many different sorts of data sets that you can make use of and also work workbooks. It’s really great and it’s absolutely.

Github

Github is really well known for collaboration but it also has tons of web pages that contain links to different ML resources. Such as machine learning papers, websites, and blogs as well. I’m going to link some of my favorite machine learning related GitHub pages. So definitely check that out.

Additionally, let’s say you have a machine learning project or product which you’re really interested in. You can try to find the source code of that on Github if it’s available and kind of try to dissect and see how it works play around with it it’s absolutely free.

Youtube Free playlists.

Youtube is great and you can learn lots from it. But when it comes to machine learning some of my favorite youtuber are

Krish Naik has tons of machine learning related videos and tutorials. He goes really in-depth into different aspects of machines. He also deeps dives with different problems as well. LINK: (819) Krish Naik – YouTube

lex Friedman’s podcast. If you just wanted to get into the world of AI and machine learning without getting bored with technical terms then, you should definitely check out lex Friedman’s podcast. He invites really amazing people into the machine learning space and it’s so interesting to watch. So definitely check that out. Link : (819) Lex Fridman – YouTube

Further read: How to start machine learning. Best guide. – ucompare.in

Conclusion

it’s definitely possible to learn machine learning for free. However, if you do end up taking a paid course. You will get more structure to your learning. which a lot of students would want. So it all depends on what you’re looking for and if you’re someone who wants to do it for free you’re going to have to kind of build your own structure.

If you have learned machine learning for free do let me know in the comment section below. And what type of resources you like the most. Thank you for visiting happy learning. Please share if you like our blogs.

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