Learn what are AutoEncoders, how they work, their usage, and finally implement Autoencoders for anomaly detection in perform fraud detection using Autoencoders in TensorFlow

*Learn what are AutoEncoders, how they work, their usage, and finally implement Autoencoders for anomaly detection.*

AutoEncoder is a generative unsupervised deep learning algorithm used for reconstructing high-dimensional input data using a neural network with a narrow bottleneck layer in the middle which contains the latent representation of the input data.

**Autoencoder consists of an Encoder and a Decoder.**

**Encoder network**: Accepts high-dimensional input data and translates it to latent low-dimensional data. The input size to an Encoder network is larger than its output size.**Decoder network**: The Decoder network receives the input from the Encoder coder’s output. Decoder’s objective is to reconstruct the input data. The output size of a Decoder network is larger than its input size.

The Autoencoder accepts high-dimensional input data, compress it down to the latent-space representation in the bottleneck hidden layer; the Decoder takes the latent representation of the data as an input to reconstruct the original input data.

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*Dimensionality Reduction. **The Encoder encodes the input into the hidden layer to reduce the dimensionality of linear and nonlinear data; hence it is more powerful than PCA. **Recommendation Engines****Anomaly Detection**: Autoencoders tries to minimize the reconstruction error as part of its training. Anomalies are detected by checking the magnitude of the reconstruction loss.**Denoising Images**: An image that is corrupted can be restored to its original version.**Image recognition**: Stacked autoencoder are used for image recognition by learning the different features of an image.**Image generation**: Variational Autoencoder(VAE), a type of autoencoders, is used to generate images.

Read about **different types of Autoencoder **[**here**](https://medium.com/datadriveninvestor/deep-learning-different-types-of-autoencoders-41d4fa5f7570)**.**

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