- training and analysis of deep neural networks using several major dl models for cv and nlp as examples (mostly in PyTorch, but also in TensorFlow)
- build a simple conv-net, optimizer, etc., in Numpy and train it
- build several custom-defined modules not included as built-in methods in PyTorch by extension on its autograd system
- homework / exam solutions with codes for several online courses on reinforcement learning
- train a deep reinforcement learning agent in OpenAI's Gym platform
- build implementations for several common RL algorithms, following major RL lib's
- implement and examine the ENAS framework in PyTorch following the original paper
-
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Pytorch implementations and training of convolutional networks
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