Hi, you can use neural network toolbox of matlab.

Have a look at :

https://www.mathworks.com/help/deeplearning/ref/classify.html

https://towardsdatascience.com/deep-reinforcement-learning-tutorial-with-open-ai-gym-c0de4471f368

https://www.analyticsvidhya.com/blog/2015/08/comprehensive-guide-regression/

Miguel Angel Imaz Lamadrid

https://cs.stanford.edu/people/eroberts/courses/soco/projects/neural-networks/Sources/index.html

https://towardsdatascience.com/a-comprehensive-guide-on-neural-networks-for-beginners-a4ca07cee1b7

https://www.analyticsvidhya.com/blog/2015/11/free-resources-beginners-deep-learning-neural-network/

https://www.quora.com/What-is-the-best-resource-to-learn-neural-networks-for-a-beginner

https://sigai.acm.org/static/aimatters/3-3/AIMatters-3-3-06-Neller.pdf

https://www.tutorialspoint.com/artificial_intelligence/artificial_intelligence_neural_networks.htm

Dear Miguel Angel Imaz Lamadrid ,

I strongly recommend you this free course of Andrew NG, who, by the way, is the founder of a several AI/educational companies (including Coursera) and Professor from Stanford: https://www.coursera.org/learn/machine-learning

Here, you can learn the mathematical fundamentals of several Machine Learning models, including Artificial Neural Networks.

Cheers!

Thanks to all for your feedback!!

Dear Miguel Angel Imaz Lamadrid

I would point you towards

1. Deeplearning.ai courses by Andrew Ng for theoretical depth.

2. Fast.ai for practical work.

Further, you can have a look at

CS231N by Stanford - Computer vision (Youtube)

CS224N - Natural Language processing (Youtube)

For frameworks,

Intro to Deep learning with Pytorch by Udacity (Free course)

Tensorflow Specialization(Deeplearning.ai)

Although, rather than just taking courses, it is better to implement stuff and learn theory on the side.

You can try working on Kaggle by making custom neural nets.

So, fast.ai and deeplearning.ai complement each other in that regard.