English | 2021 | ISBN-13 : 979-8720214708 | 186 pages | PDF, EPUB, AZW3 | 23.17 MB
This book is a collection of notes and sample codes written by the author while he was learning Neural Networks in Machine Learning.
Topics include Neural Networks (NN) concepts: nodes, layers, activation functions, learning rates, training sets, etc.; deep playground for classical neural networks; building neural networks with Python; walking through Tariq Rashi's 'Make Your Own Neural Network' source code; using 'TensorFlow' and 'PyTorch' machine learning platforms; understanding CNN (Convolutional Neural Network), RNN (Recurrent Neural Network), GNN (Graph Neural Network). Updated in 2020 (Version 1.20) with Deep Playground tutorials.For latest updates and free sample chapters, visit
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