Free machine learning books / courses to start your dream career
Learning should be available and not expensive. That’s why I compiled a list of notable learning resources.
After learning linear algebra, statistics & calculus you wonder where you should go next. That’s why I created a comprehensive list on where you could go to go next. without particular order.
d2l.ai
Dive into Deep Learning is a comprehensive guide on a lot of machine learning algorithms. All made in the beloved programming language Python. This popular book has been adopted by 175 universities from 40 countries. It teaches different approaches with different frameworks such as TensorFlow & PyTorch.
Andrew ng — Machine learning
Unlike the other learning material here this is teaches in Matlab / octave. This course is also the oldest but still teaches machine learning in beginner friendly way without being too mathematical. If you just started & are not sure if your mathematics skills are good enough I would recommend you to start with this course. This course is free but you can also pay for it and get a certificate which you can put on your LinkedIn.
Google Machine Learning Crash Course
About 15 hours of learning material with real world case studies. Here you will learn machine learning with video’s in TensorFlow. If you are someone who likes / learns faster with video’s this is something for you. Personally I have not tried this crash course but it looks promising.
Kaggle courses
On Kaggle there are some micro-courses which can teach you a verity of new tools / techniques. Each micro course also rewards you with a certificate which you can display on your LinkedIn. Kaggle is also the place where you can test your machine learning skills on various of problems. This is a good place to test your skill & compare yourself to the best (In a non toxic manner).
NeuralNetworksAndDeepLearning.com
This is a free online book which teaches machine basic machine learning for Python. This book doesn’t Tensorflow or PyTorch but a more “lower-level” library called theano. Since there is less abstraction you have to do a lot more yourself and get a better feeling of what is going on inside the higher level libraries.
If you got any other great sources please leave a comment and I’ll add them to this list.
