Gain a comprehensive understanding of deep learning and neural networks in this 34-minute video tutorial. Explore key concepts such as convolution, max pooling, batch normalization, dropout, flatten, activation, optimizer, and loss function. Delve into the fundamentals of TensorFlow, hidden layers, neurons, and epochs. Access accompanying code on GitHub to enhance your learning experience and practical application of these concepts in microscopy-related Python projects.
Overview
Syllabus
Introduction
Recap of previous tutorials
tensorflow
convolution
dropout
flattening
hidden layers
neuron
optimizer
loss function
Epoch
Taught by
DigitalSreeni
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