Autoencoder

Introduction To Autoencoders In Machine Learning.

Autoencoders are neural networks designed in a way they can learn any existing structure in a dataset. They create a compact representation of the data we can leverage later in different applications. Some applications where you can leverage autoencoders: anomaly detection, image denoisin

From playlist Machine Learning Techniques

Autoencoders - EXPLAINED

Data around us, like images and documents, are very high dimensional. Autoencoders can learn a simpler representation of it. This representation can be used in many ways: - fast data transfers across a network - Self driving cars (Semantic Segmentation) - Neural Inpainting: Completing sect

From playlist Algorithms and Concepts

Autoencoders - Ep. 10 (Deep Learning SIMPLIFIED)

Autoencoders are a family of neural nets that are well suited for unsupervised learning, a method for detecting inherent patterns in a data set. These nets can also be used to label the resulting patterns. Deep Learning TV on Facebook: https://www.facebook.com/DeepLearningTV/ Twitter: ht

From playlist Deep Learning SIMPLIFIED

Autoencoders Tutorial | Autoencoders In Deep Learning | Tensorflow Training | Edureka

** AI & Deep Learning with Tensorflow Training: www.edureka.co/ai-deep-learning-with-tensorflow ** This Edureka video of "Autoencoders Tutorial" provides you with a brief introduction about autoencoders and how they compress unsupervised data. You will get detailed information on the diff

From playlist Introduction to Deep Learning

What Are Autoencoders? | Autoencoders Using TensorFlow | Deep Learning Using TensorFlow | Edureka

** AI & Deep Learning with Tensorflow Training: https://goo.gl/vDxgi5 ** ) This Edureka tutorial video of "What are autoencoders" provides you with a brief introduction about autoencoders and how they compress unsupervised data. You will see the various applications and types of autoencode

From playlist Deep Learning With TensorFlow Videos

What is an Autoencoder? | Two Minute Papers #86

Autoencoders are neural networks that are capable of creating sparse representations of the input data and can therefore be used for image compression. There are denoising autoencoders that after learning these sparse representations, can be presented with noisy images. What is even better

From playlist Introduction to Deep Learning

Understanding geometric attributes with autoencoders. - Newson - Workshop 3 - CEB T1 2019

Alasdair Newson (Télécom ParisTech) / 03.04.2019 Understanding geometric attributes with autoencoders. Autoencoders are neural networks which project data to and from a lower dimensional latent space, the projection being learned via training on the data. While these networks produce im

From playlist 2019 - T1 - The Mathematics of Imaging

Neural networks [6.4] : Autoencoder - linear autoencoder

From playlist Neural networks class - Université de Sherbrooke

Transformers - Part 3 - Encoder

In this video, we present the encoder layer in the transformer. Important components of this presentation is that we introduce multi-head attention, positional encodings and the architecture of the encoder blocks that appear inside the encoder. The video is part of a series of videos on t

From playlist A series of videos on the transformer

Masked Autoencoders Are Scalable Vision Learners – Paper explained and animated!

“Masked Autoencoders Are Scalable Vision Learners” paper explained by Ms. Coffee Bean. Say goodbye to contrastive learning and say hello (again) to autoencoders in #ComputerVision! Love the simple, yet elegant idea! ► Check out our sponsor: Weights & Biases 👉 https://wandb.me/ai-coffee-br

From playlist The Transformer explained by Ms. Coffee Bean

27. Variational Autoencoders

Generative machine learning models have the potential to allow us to move beyond screening to true materials discovery. Generative adversarial networks (GANs) are one powerful tool and variational autoencoders (VAEs) are another. This video descrbies autoencoders, latent space, reparameter

From playlist Materials Informatics

Variational Autoencoders - EXPLAINED!

In this video, we are going to talk about Generative Modeling with Variational Autoencoders (VAEs). The explanation is going to be simple to understand without a math (or even much tech) background. However, I also introduce more technical concepts for you nerds out there while comparing V

From playlist Variational AutoEncoders

Deep Learning with Tensorflow - Introduction to Autoencoders

Enroll in the course for free at: https://bigdatauniversity.com/courses/deep-learning-tensorflow/ Deep Learning with TensorFlow Introduction The majority of data in the world is unlabeled and unstructured. Shallow neural networks cannot easily capture relevant structure in, for instance,

From playlist Deep Learning with Tensorflow

Neural networks [6.7] : Autoencoder - contractive autoencoder

From playlist Neural networks class - Université de Sherbrooke

Deep Learning Full Course - Learn Deep Learning in 6 Hours | Deep Learning Tutorial | Edureka

** AI & Deep Learning with TensorFlow (Use Code: YOUTUBE20): https://www.edureka.co/ai-deep-learning-with-tensorflow ** This Edureka Deep Learning Full Course video will help you understand and learn Deep Learning & Tensorflow in detail. This Deep Learning Tutorial is ideal for both beginn

From playlist Deep Learning With TensorFlow Videos