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Deep Learning Wizard Courses
Practical Deep Learning with PyTorch
3.9 (1,727 Reviews)
Provider: Udemy
Time: 6.5h- 2018
$11.99
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Most Recent Review
It's easy to criticize from the stands. What's hard... is doing something. I think the course delivers what it promised. The author made a small regression tour across different domains at the beginning, and, as a result - it derailed expectations from this course. In my opinion, RNN and LSTM were trained in the wrong data sets - By design, they should be trained on time series instead of MNIST. As a result, it gives a false understanding of why we are doing what we are doing. Overall opinion is somewhat average - it could be additional information if you are learning AI. It does explain the Math aspect of AI models. The course could be updated, but some code snippets are deprecated and should not be used in the future. I think the fair price for this curse is somewhat around Starbucks Coffee.
- Review by Eugeniusz Siedlecki on Practical Deep Learning with PyTorch
Instructor Bio
Currently I am leading artificial intelligence with my colleagues in ensemblecap, an AI hedge fund based in Singapore comprising quants and traders from JPMorgan and Nomura. I have built the whole AI tech stack in a production environment with rigorous time-sensitive and fail-safe software testing powering multi-million dollar trades daily.
I am also an NVIDIA Deep Learning Institute instructor leading all deep learning workshops in NUS, Singapore and conducting workshops across Southeast Asia.
My passion for enabling anyone to leverage on deep learning has led to the creation of Deep Learning Wizard where I have taught and still continue to teach more than 2000 students in over 60 countries around the world. The course is recognized by Soumith Chintala, Facebook AI Research, and Alfredo Canziani, Post-Doctoral Associate under Yann Lecun, as the first comprehensive PyTorch Video Tutorial.
In my free time, I’m into deep learning research with researchers based in NExT++ (NUS) led by Chua Tat-Seng and MILA led by Yoshua Bengio. I was previously conducting research in meta-learning for hyperparameter optimization for deep learning algorithms in NExT Search Centre that is jointly setup between National University of Singapore (NUS), Tsinghua University and University of Southampton led by co-directors Prof Tat-Seng Chua (KITHCT Chair Professor at the School of Computing), Prof Sun Maosong (Dean of Department of Computer Science and Technology, Tsinghua University), and Prof Dame Wendy Hall (Director of the Web Science Institute, University of Southampton). During my time there, I managed to publish in top-tier conferences and workshops like ICML and IJCAI.
