## Deep Learning Notes PDF

Free Deep Learning notes pdf are provided here for Deep Learning students so that they can prepare and score high marks in their Deep Learning exam.

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Topics in our Deep Learning Notes PDF

The topics we will cover in these **Deep Learning Notes PDF** will be taken from the following list:

**Introduction: **Historical context and motivation for deep learning; basic supervised classification task, optimizing logistic classifier using gradient descent, stochastic gradient descent, momentum, and adaptive sub-gradient method.

**Neural Networks: **Feedforward neural networks, deep networks, regularizing a deep network, model exploration, and hyper parameter tuning.

**Convolution Neural Networks: **Introduction to convolution neural networks: stacking, striding and pooling, applications like image, and text classification.

**Sequence Modeling: **Recurrent Nets: Unfolding computational graphs, recurrent neural networks (RNNs), bidirectional RNNs, encoder-decoder sequence to sequence architectures, deep recurrent networks, LSTM networks.

**Autoencoders: **Undercomplete autoencoders, regularized autoencoders, sparse autoencoders, denoising autoencoders, representational power, layer, size, and depth of autoencoders, stochastic encoders and decoders.

**Structuring Machine Learning Projects: **Orthogonalization, evaluation metrics, train/dev/test distributions, size of the dev and test sets, cleaning up incorrectly labeled data, bias and variance with mismatched data distributions, transfer learning, multi-task learning.

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## Benefits of FREE Deep Learning Notes PDF

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Q: How to download Deep Learning notes pdf?

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