Autoencoders

Generative NLP with Variational AutoEncoders  eBooks & eLearning

Posted by IrGens at June 7, 2024
Generative NLP with Variational AutoEncoders

Generative NLP with Variational AutoEncoders
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 4h 33m | 698 MB
Instructor: Axel Sirota

Machine Learning : Introduction To Variational Autoencoders  eBooks & eLearning

Posted by ELK1nG at Aug. 26, 2022
Machine Learning : Introduction To Variational Autoencoders

Machine Learning : Introduction To Variational Autoencoders
Published 8/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 563.30 MB | Duration: 1h 38m

Autoencoders and Variational Autoencoders from scratch | Auto-Encoding Variational Bayes paper | Deep Learning | PyTorch

Deep Learning: GANs and Variational Autoencoders  eBooks & eLearning

Posted by igor_lv at Nov. 3, 2018
Deep Learning: GANs and Variational Autoencoders

Deep Learning: GANs and Variational Autoencoders
MP4 | Video: 1280x720 | Duration: 7 Hours | 500 MB
Author: Lazy Programmer Inc. | Language: English | Skill level: Intermediate

Generative Adversarial Networks and Variational Autoencoders in Python, Theano, and Tensorflow

Master Autoencoders In Keras  eBooks & eLearning

Posted by ELK1nG at Aug. 5, 2022
Master Autoencoders In Keras

Master Autoencoders In Keras
Last updated 6/2021
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 541.29 MB | Duration: 1h 25m

Complete course on Autoencoders and its variants with implementation in Keras

neural networks for autoencoders and recommender systems  eBooks & eLearning

Posted by Sigha at Nov. 11, 2020
neural networks for autoencoders and recommender systems

neural networks for autoencoders and recommender systems
Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 44100 Hz, 2ch | Size: 873 MB
Genre: eLearning Video | Duration: 16 lectures (1 hour, 48 mins) | Language: English

How to build autoencoders and recommender systems with neural networks. Machine learning hands on data science class

Essentials of Deep Learning and AI: Experience Unsupervised Learning, Autoencoders  eBooks & eLearning

Posted by Free butterfly at Sept. 18, 2023
Essentials of Deep Learning and AI: Experience Unsupervised Learning, Autoencoders

Essentials of Deep Learning and AI: Experience Unsupervised Learning, Autoencoders, Feature Engineering, and Time Series Analysis with TensorFlow, Keras, and scikit-learn (English Edition) by Shashidhar Soppin, Dr. Manjunath Ramachandra, B N Chandrashekar
English | November 25, 2021 | ISBN: 9391030351 | 394 pages | MOBI | 4.97 Mb
Essentials of Deep Learning and AI: Experience Unsupervised Learning, Autoencoders, Feature Engineering, and Time Series Analys

Essentials of Deep Learning and AI
by Soppin, Shashidhar;Ramachandra, Manjunath;Chandrashekar, B. N.;

English | 2021 | ISBN: ‎ 9391030351 | 345 pages | True EPUB, PDF Conv. | 10.45 MB
Learn Python Generative AI: Journey from autoencoders to transformers to large language models (English Edition)

Learn Python Generative AI: Journey from autoencoders to transformers to large language models (English Edition) by Zonunfeli Ralte, Indrajit Kar
English | February 1, 2024 | ISBN: 9355518978 | 348 pages | MOBI | 3.22 Mb
Learn Python Generative AI: Journey From Autoencoders to Transformers to Large Language Models

Learn Python Generative AI: Journey From Autoencoders to Transformers to Large Language Models by Zonunfeli Ralte, Indrajit Kar
English | February 29th, 2024 | ISBN: 9355518978 | 348 pages | True EPUB (Retail Copy) | 7.25 MB

This book researches the intricate world of generative Artificial Intelligence, offering readers an extensive understanding of various components and applications in this field.

Unsupervised Deep Learning in Python  eBooks & eLearning

Posted by Sigha at March 11, 2019
Unsupervised Deep Learning in Python

Unsupervised Deep Learning in Python
.MP4 | Video: 1280x720, 30 fps(r) | Audio: AAC, 48000 Hz, 2ch | 2.69 GB
Duration: 10.5 hours | Genre: eLearning Video | Language: English

Theano / Tensorflow: Autoencoders, Restricted Boltzmann Machines, Deep Neural Networks, t-SNE and PCA.