For neural network theory, I'm very fond of http://neuralnetworksanddeeplearning.com, but you'll need calculus and some linear algebra to understand it. Source: 5 months ago
Alternatively, building them from scratch in numpy is definitely possible and an excellent way to learn the fundamentals. It will take some time though (debugging issues with a hand-rolled LSTM is very, very painful). There's a zillion tutorials/books out there (I think I started with http://neuralnetworksanddeeplearning.com). Source: 5 months ago
- http://neuralnetworksanddeeplearning.com/ The Watch the Caltech telecourse. - Source: Hacker News / 9 months ago
Neural Networks and Deep Learning, a free online book. http://neuralnetworksanddeeplearning.com/. - Source: Hacker News / 10 months ago
Many years ago I was studying deep learning using this resource: * http://neuralnetworksanddeeplearning.com/ I decided to try to implement everything from scratch in Elixir (after initially doing all the math with pen and paper on a trivial example to get the feel of it). Obviously pure elixir was extremely slow, so I started creating NIFs to pass over matrix multiplication to OpenBLAS. Then I was thinking more... - Source: Hacker News / 11 months ago
This book is free and has a great section on backpropagation, which is how neural networks adjust their weights, including the math. The code snippets are in python 2 though so just be careful when copying and pasting. Http://neuralnetworksanddeeplearning.com/. Source: 12 months ago
Current idea:-solve this books exercises, write it up in Latex, put it on githttp://neuralnetworksanddeeplearning.com-tidy up my ML/DL university assignments and put them on Git-after that, road to Kaggle Master/Grandmaster?-do a full ML+MLOps personal project and put it on Git/online. Source: 12 months ago
For AI, I personally recommend http://neuralnetworksanddeeplearning.com/ and the courses on https://www.fast.ai/. Source: about 1 year ago
ChatGPT feels like a good example, I think 6 months ago that those who weren't in the know would be able to predict something like that. I know I wouldn't be able to, and I even build some small neural nets for fun and read Neural Networks and Deep Learning [1]. I am by no means an expert in the field, but I know some basics and have programmed in all kinds of languages, watched 2 Minute Papers quite a bit and yet... - Source: Hacker News / about 1 year ago
Neural networks and deep learning Http://neuralnetworksanddeeplearning.com/. Source: about 1 year ago
Gilbert Strang wrote a book called “Linear Algebra and Learning From Data” that’s available for free download, I would highly recommend that. I’ll also recommend the free online “book” by Michael Nielsen, found at http://neuralnetworksanddeeplearning.com. Source: about 1 year ago
An online book by Michael Nielsen : http://neuralnetworksanddeeplearning.com/ It starts from basics and builds a CNN to recognize handwritten digits. I found it very helpful during my start of the journey. - Source: Hacker News / over 1 year ago
Http://neuralnetworksanddeeplearning.com (full text) The first chapter walks through a neural network that recognizes handwritten digits implemented in a little over 70 lines of Python and leaves you with a very satisfying basic understanding of how neural networks operate and how they are trained. - Source: Hacker News / over 1 year ago
Machine learning is an enormous field, and if you are after a explanation/exploration from the ground up, then Kevin Murphy's Probabilistic Machine Learning: An Introduction is very good, but a bit of a tome. If instead, you want to focus on neural networks, I found Michael Nielsen's Neural Networks and Deep Learning, available at http://neuralnetworksanddeeplearning.com/, an excellent resource for implementing... - Source: Hacker News / over 1 year ago
You could have a look at http://neuralnetworksanddeeplearning.com. Back in the day, I built a basic neural network from scratch (with plain NumPy) and trained it using backpropagation following this book/site. Surprisingly, I was able to make it recognize my own handwriting (using MNIST was too boring). It was a basic feedforward neural network, though, not a convolutional one or anything fancy that's specifically... Source: over 1 year ago
This book has some good explanations on these concepts Http://neuralnetworksanddeeplearning.com. Source: over 1 year ago
This is the best starting point: http://neuralnetworksanddeeplearning.com/ Then: https://m.youtube.com/playlist?list=PL5-TkQAfAZFbzxjBHtzdVCWE0Zbhomg7r and/or: https://www.fast.ai/posts/2022-07-21-dl-coders-22.html. - Source: Hacker News / over 1 year ago
I read now the excellent book recommended by 3b1b It’s available for free here and you can donate if you find it useful. Source: over 1 year ago
It doesn't cover autoencoders, but this is a nice easy intro to deep learning. Source: almost 2 years ago
I think you definitely may want to read this: http://neuralnetworksanddeeplearning.com/ the first chapters may enlighten you on the basics. Source: almost 2 years ago
If you are keen on getting your hands a little dirty, I'd recommend you read and code-along with http://neuralnetworksanddeeplearning.com/. Source: about 2 years ago
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