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Fundamentals of Probability and Statistics for Machine Learning

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Understanding Deep Learning: Building Machine Learning Systems with PyTorch and TensorFlow: From Neural Networks (CNN, DNN, GNN, RNN, ANN, LSTM, GAN) to Natural Language Processing (NLP)

Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms

Grokking Machine Learning

The Principles of Deep Learning Theory: An Effective Theory Approach to Understanding Neural Networks

Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition