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README.md

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 <!--# Collection of notes on {ml.nn-zero2hero}-->
 ### Disclaimer: All the rights of these codes and resources belong to their original authors. I am compiling a collection for self-learning purposes and to build tools by myself using the knowledge.
 
-My notes and learnings following the [nn_zero_to_hero](https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ) guide by Andrej Karpathy and the open-source notebooks available on [Hands-On Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2](https://github.com/ageron/handson-ml3) by Aurelien Geron. Personally, I found these to be two of the best resources available on this subject, purely from an applied learning stand point. I should also look into getting a better theoretical background on the subject as well. I learned how to build these notes like this thanks to [](https://github.com/mobook/MO-book)
+My notes and learnings following the [nn_zero_to_hero](https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ) guide by Andrej Karpathy and the open-source notebooks available on [Hands-On Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2](https://github.com/ageron/handson-ml3) by Aurelien Geron. Personally, I found these to be two of the best resources available on this subject, purely from an applied learning stand point. I should also look into getting a better theoretical background on the subject as well. I learned how to build these notes like this thanks to the source repository for the [Hands-On Mathematical Optimization with Python](https://github.com/mobook/MO-book).
 
 Other resources include (but not limited to),
 - The [DeepLearning.ai](https://deeplearning.ai/) courses on the Machine Learning / Deep Learning Specialization by Andrew Ng