• Deep Learning with fast.ai

    Machine Learning Course III @ Coderbunker



    On the internet you can find a lot of resources that promise you that they can teach you machine learning. But that is a tough project and many give up on the way. At coderbunker we created a workshop to work together carefully selected resources along with experienced mentors. Don’t get stuck, get stuff done with our motivated team!

    If you get through this ambitious six months program, we are confident to say that you can call yourself a machine learning engineer.

    We base the co-learning sessions on fast.ai. It is a very challenging workshop during which you are going to make exciting machine learning experiments.

    - Requirements -

    • At ease with python programming

    • At ease with linux command line

    • Familiar with keras, matplotlib, numpy, pandas (better if you have joined our workshop on that topic)

    • Be able to configure a remote server with a GPU

    - Goal -


    • Good understanding of multilayer perceptron, activation functions, convolution neural networks, recurrent neural networks, collaborative filtering model, popular types of loss functions, optimizers.

    • Comfortable with putting all those above understandings into deployment and know how to experiment with your curiosity on model structures without any template.

    • Capable of understanding at least 2 papers you can code, and apply the knowledge you learn from the papers to code.

    • Capable of implementing neural networks to new problems you haven’t seen the code of.

    • Can use tools like tensorboard to visualize your work.

    • Capable of constructing your own keras layer, loss function and metrics.

    • In a good state to participate any Kaggle competition.

    - Course Materials -


    More information coming soon...

    - Course Program -


    More information coming soon...

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