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

Lesson 1: Building Neural Networks with Keras: An Introduction

Exploring the Cosmos with Neural Networks

Building Your Own Neural Network Spacecraft

Crafting a Neural Network with Keras

Lesson 2: Understanding Forward Propagation in Neural Networks

Iris Flower Classification with Neural Networks

Adding Hidden and Output Layers and Compiling the Neural Network

Building and Training a Neural Network

Lesson 3: Understanding and Implementing Autoencoders with Keras for Dimensionality Reduction

Exploring Autoencoders with Digit Reconstruction

Autoencoder Decoder Adjustment

Autoencoder Space Odyssey: Compress and Reconstruct

Lesson 4: Fine-Tuning Autoencoders: Mastering Hyperparameters

Observing Autoencoder Performance with Different Learning Rates

Autoencoder Activation Function Exploration

Creating an Autoencoder with Optimal Learning Rate

Lesson 5: Understanding Optimizers in Autoencoders

Navigating the Cosmos of Optimizers

Setting Up the Autoencoder Optimizer

Navigating the Cosmos of Optimizers

Interested in this course? Learn and practice with Cosmo!

Practice is how you turn knowledge into actual skills.