Deep Learning (for Audio) with Python: Difference between revisions
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"In this series, I explore theory and implementation of deep learning in the Python programming language. The course focuses on applications of deep learning for audio and music, but discusses general algorithms and principles applicable to any problem. I use TensorFlow." | |||
= Deep Learning (for Audio) with Python: Course Overview = | = Deep Learning (for Audio) with Python: Course Overview = | ||
<evlplayer id="player1" w="480" h="360" service="youtube" defaultid="fMqL5vckiU0" /> | <evlplayer id="player1" w="480" h="360" service="youtube" defaultid="fMqL5vckiU0" /> | ||
Revision as of 22:38, 29 August 2021
"In this series, I explore theory and implementation of deep learning in the Python programming language. The course focuses on applications of deep learning for audio and music, but discusses general algorithms and principles applicable to any problem. I use TensorFlow."
Deep Learning (for Audio) with Python: Course Overview[edit]
AI, machine learning and deep learning[edit]
Implementing an artificial neuron from scratch[edit]
Vector and matrix operations[edit]
Computation in neural networks[edit]
Implementing a neural network from scratch in Python[edit]
Training a neural network: Backward propagation and gradient descent[edit]
TRAINING A NEURAL NETWORK: Implementing backpropagation and gradient descent from scratch[edit]
How to implement a (simple) neural network with TensorFlow 2[edit]
Understanding audio data for deep learning[edit]
Preprocessing audio data for Deep Learning[edit]
Music genre classification: Preparing the dataset[edit]
Implementing a neural network for music genre classification[edit]
SOLVING OVERFITTING in neural networks[edit]
Convolutional Neural Networks Explained Easily[edit]
How to Implement a CNN for Music Genre Classification[edit]
Recurrent Neural Networks Explained Easily[edit]
Long Short Term Memory (LSTM) Networks Explained Easily[edit]