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We believe that the fact that we currently require high school math, one year of coding experience, and seven weeks of study to become a ...

I have been using both fastai and pytorch interchangeably for quite a while now, and they work together well. Fastai's goal is to be practical, so they include a bunch of concepts rarely discussed in academia but are quite effective, like super convergence (the fit one cycle thing), active learning and more data augmentation techniques.

Fast ai is (at least was) a bit like the keras of pytorch. If you want to use tensorflow you won't find the classes transferable directly, but ...

FastAi Code documentation is good, not great, and some of the functions and parameters could be a bit more descriptive on the website but the forum has some excellent contributors, including Jeremy. Be aware that the ML course is from 2018 and uses V0.7 of the library. The latest DL course from January uses V1.0 and is not backwards compatible.

fast.ai offers a fantastic course and very comprehensive and great course materials. It is totally worth it. I personally suggest to take deeplearning.ai's specialization along with it as well. fast.ai teaches using a top-down approach, which will force you to do things by hand, practically, which is of great value.. About TF vs. PyTorch, frameworks don't matter much when it comes to learning ...

I like pytorch and tensoflow way more. PyTorch is my go to. More control and not everything is under the hood unlike fastai. But tbh I haven't seen fastai in quite some while so I could be wrong. It just seemed very black box sort of thing to me which I didn't really like.

fastai is a platform built on top of pytorch (like keras for tensorflow). The main difference is that you have to write many things from scratch ...

fastai for PyTorch is NOT what Keras is for TF. The better comparison would be PyToch = Keras. In both frameworks it is easy to define neural ...

In the other hands, TensorFlow has a lot of documentation online compared to PyTorch. Although Fast.ai courses are great quality, ...

I appreciate the role both fastai and PyTorch Lightning have played in shaping the ... Although, pytorch is amazing compared to others.

About TF vs. PyTorch, frameworks don't matter much when it comes to learning them. If you learn one well, and your fundamental understanding ...

So i understand that fast.ai is a wrapper for the pytorch ... learning and math behind it” vs tensorflow may be just solely implementations.

I used the FastAI lib and it shot straight to a 90%. ... [D] Keras vs Pytorch - in depth comparison of opposing approaches · deepsense.ai.

Shows the Silver Award... and that's it. Gives 100 Reddit Coins and a week of r/lounge access and ad-free When you come across a feel-good thing ...

FastAi vs Pytorch. Which do you prefer and why? I want to know the pros and cons. I haven't dived much into either fast.ai or PyTorch, but I have played around with both once or twice. I am trying to dive into either one now that schools have moved online due to the coronavirus and I have some time on my hands.

fastai is basically another layer on top of PyTorch that gives you a lot new functionality around your neural network, such as visualization methods for your data, more ways of loading and splitting data, infering the number of classes from the dataset your provide and it extends the training utilities by a concept called "callbacks" (which keras also has but pytorch doesnt).