Learning Generative Adversarial Networks

Author: sddd on 8-02-2018, 23:51
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Learning Generative Adversarial Networks
Learning Generative Adversarial Networks
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 2 Hours | Lec: | 460 MB
Genre: eLearning | Language: English


Learning Generative Adversarial Networks

Generative models are gaining a lot of popularity among data scientists, mainly because they facilitate the building of AI systems that consume raw data from a source and automatically build an understanding of it.
Unlike supervised learning methods, generative models do not require labeling data, which makes for an interesting system to use. This video will help you build and analyze deep learning models and apply them to real-world problems. It will help readers develop intelligent and creative application from a wide variety of datasets, mainly focusing on visuals or images.
The video begins with the basics of generative models, as you get to know the theory behind Generative Adversarial Networks and its building blocks. In this video, you'll see how to overcome the problem of text-to-image synthesis with GANs, using libraries such as Tensorflow, Keras, and PyTorch.
Download link :
(If you need these, buy and download immediately before they are delete)
Links are Interchangeable - Single Extraction - Premium is support resumable
Learning Generative Adversarial Networks
Learning Generative Adversarial Networks
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 2 Hours | Lec: | 460 MB
Genre: eLearning | Language: English


Learning Generative Adversarial Networks

Generative models are gaining a lot of popularity among data scientists, mainly because they facilitate the building of AI systems that consume raw data from a source and automatically build an understanding of it.
Unlike supervised learning methods, generative models do not require labeling data, which makes for an interesting system to use. This video will help you build and analyze deep learning models and apply them to real-world problems. It will help readers develop intelligent and creative application from a wide variety of datasets, mainly focusing on visuals or images.
The video begins with the basics of generative models, as you get to know the theory behind Generative Adversarial Networks and its building blocks. In this video, you'll see how to overcome the problem of text-to-image synthesis with GANs, using libraries such as Tensorflow, Keras, and PyTorch.
Download link :
(If you need these, buy and download immediately before they are delete)
Links are Interchangeable - Single Extraction - Premium is support resumable
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