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 = | ||
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= AI, machine learning and deep learning = | = AI, machine learning and deep learning = | ||
<evlplayer id="player1" w="480" h="360" service="youtube" defaultid="1LLxZ35ru_g" /> | <evlplayer id="player1" w="480" h="360" service="youtube" defaultid="1LLxZ35ru_g" /> | ||
= Implementing an artificial neuron from scratch = | = Implementing an artificial neuron from scratch = | ||
<evlplayer id="player1" w="480" h="360" service="youtube" defaultid="qxIaW-WvLDU" /> | <evlplayer id="player1" w="480" h="360" service="youtube" defaultid="qxIaW-WvLDU" /> | ||
= Vector and matrix operations = | = Vector and matrix operations = | ||
<evlplayer id="player1" w="480" h="360" service="youtube" defaultid="FmD1S5yP_os" /> | <evlplayer id="player1" w="480" h="360" service="youtube" defaultid="FmD1S5yP_os" /> | ||
= Computation in neural networks = | = Computation in neural networks = | ||
<evlplayer id="player1" w="480" h="360" service="youtube" defaultid="QUCzvlgvk6I" /> | <evlplayer id="player1" w="480" h="360" service="youtube" defaultid="QUCzvlgvk6I" /> | ||
= Implementing a neural network from scratch in Python = | = Implementing a neural network from scratch in Python = | ||
<evlplayer id="player1" w="480" h="360" service="youtube" defaultid="0oWnheK-gGk" /> | <evlplayer id="player1" w="480" h="360" service="youtube" defaultid="0oWnheK-gGk" /> | ||
= Training a neural network: Backward propagation and gradient descent = | = Training a neural network: Backward propagation and gradient descent = | ||
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= TRAINING A NEURAL NETWORK: Implementing backpropagation and gradient descent from scratch = | = TRAINING A NEURAL NETWORK: Implementing backpropagation and gradient descent from scratch = | ||
<evlplayer id="player1" w="480" h="360" service="youtube" defaultid="Z97XGNUUx9o" /> | <evlplayer id="player1" w="480" h="360" service="youtube" defaultid="Z97XGNUUx9o" /> | ||
= How to implement a (simple) neural network with TensorFlow 2 = | = How to implement a (simple) neural network with TensorFlow 2 = | ||
<evlplayer id="player1" w="480" h="360" service="youtube" defaultid="JdXxaZcQer8" /> | <evlplayer id="player1" w="480" h="360" service="youtube" defaultid="JdXxaZcQer8" /> | ||
= Understanding audio data for deep learning = | = Understanding audio data for deep learning = | ||
<evlplayer id="player1" w="480" h="360" service="youtube" defaultid="m3XbqfIij_Y" /> | <evlplayer id="player1" w="480" h="360" service="youtube" defaultid="m3XbqfIij_Y" /> | ||
= Preprocessing audio data for Deep Learning = | = Preprocessing audio data for Deep Learning = | ||
<evlplayer id="player1" w="480" h="360" service="youtube" defaultid="Oa_d-zaUti8" /> | |||
= Music genre classification: Preparing the dataset = | |||
<evlplayer id="player1" w="480" h="360" service="youtube" defaultid="szyGiObZymo" /> | <evlplayer id="player1" w="480" h="360" service="youtube" defaultid="szyGiObZymo" /> | ||
= Implementing a neural network for music genre classification = | |||
<evlplayer id="player1" w="480" h="360" service="youtube" defaultid="_xcFAiufwd0" /> | |||
= SOLVING OVERFITTING in neural networks = | |||
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= Convolutional Neural Networks Explained Easily = | |||
<evlplayer id="player1" w="480" h="360" service="youtube" defaultid="t3qWfUYJEYU" /> | |||
= How to Implement a CNN for Music Genre Classification = | |||
<evlplayer id="player1" w="480" h="360" service="youtube" defaultid="dOG-HxpbMSw" /> | |||
= Recurrent Neural Networks Explained Easily = | |||
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= Long Short Term Memory (LSTM) Networks Explained Easily = | |||
<evlplayer id="player1" w="480" h="360" service="youtube" defaultid="eCvz-kB4yko" /> | |||
= How to Implement an RNN-LSTM Network for Music Genre Classification = | |||
<evlplayer id="player1" w="480" h="360" service="youtube" defaultid="4nXI0h2sq2I" /> | |||
Latest revision as of 22:41, 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]