Thanks! And... where next?

I just finished the Deep Learning Specialization, and I would like to say a word of thanks to Andrew and the whole team behind the specialization. I really enjoyed it, and I feel it is a really good introduction to the field, with a nice balance of breadth and depth of topics. It is well designed, and has clearly been created (and is maintained) with tremendous thought, effort and commitment. Kudos to all involved! I shall certainly be recommending the specialization to anyone who’s interested in starting into Deep Learning.

What I aim to do next is to start getting hands-on with putting this all into practice, doing my own exercises and mini-projects, and starting to get a feel for how it actually works when you are building your own models, without the excellent guidance you get in the specialization assessments!

I haven’t really started looking for resources for this yet, but I imagine the Tensorflow “Getting Started” pages will be a good first step, perhaps also something like Kaggle? If you do have any advice on good places to look for exercises, practice data-sets, and ML challenges, I would be grateful for suggestions.

Thanks again, and keep up the good work!


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I have the same question.

I don’t feel comfortable with tensorflow and keras at the moment.

Where should I get started in order to master tensorflow and keras systematically ? Or one step back, what should I learn next ?

I tried DeepLearning.AI TensorFlow Developer , I’ve finished 3 out of 4 courses of this specialization, but I would say this is not a good course…there was little taught in the specialization.

Maybe some kaggle competition’s jupyter notes would help.