Mastering Dimensionality Reduction with Python

Enigmatic Autoencoders for Dimensionality Reduction

In this course, explore how autoencoders can compress and reconstruct data, offering insights into unsupervised learning for dimensionality reduction.

Lessons and practices

Exploring the Cosmos with Neural Networks

Building Your Own Neural Network Spacecraft

Crafting a Neural Network with Keras

Iris Flower Classification with Neural Networks

Adding Hidden and Output Layers and Compiling the Neural Network

Building and Training a Neural Network

Exploring Autoencoders with Digit Reconstruction

Autoencoder Decoder Adjustment

Autoencoder Space Odyssey: Compress and Reconstruct

Observing Autoencoder Performance with Different Learning Rates

Autoencoder Activation Function Exploration

Creating an Autoencoder with Optimal Learning Rate

Navigating the Cosmos of Optimizers

Setting Up the Autoencoder Optimizer

Navigating the Cosmos of Optimizers

Interested in this course? Learn and practice with Cosmo!

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