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Machine learning from scratch without libraries

Backpropagation, Neural Networks, Regression models, Classification models, CNNs, SVM, Trees, Forests, etc. - all writtern from scratch without PyTorch or TensorFlow.

Altough, I am briefly covering the theory (and mathematics) behind each of the models, it is required for the reader to already have some basic knowledge in machine learning and the models in question.

Machine Learning Roadmap

NB: I will be updating this roadmap on the fly - after adding new and new models.

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Backprop, NNs, Regression models, Classification models, etc. - all writtern from scratch without PyTorch or TensorFlow

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