Deep Blue
Some words about the project. All animations were rendered in 24K HDR and downconverted to 8K HDR for the Planetarium. The footage is so sharp that the first time we observed our 8K TV playing back the footage, how hard was for the TV to solve all sharpness and resolution. Why 24K - 16K? Simply put after experimenting with 8K animations we found that rendering in higher resolutions and downconverting it back to 8K the picture looks better has more information and it looks sharper along with the HDR. Finally seeing the film on a big dome at the Planetarium in 24K - 8K is clearer than native 8K and the audiences are getting more immersed as a result.
The project took 3 months to render.

Credits

Produced by Gala Media
Directed by J.A.G
Narrated by Ravin Wong "RawVintage"
Animated by J.A.G
Edited by J.A.G
Music by Jennifer Athena Galatis

Soundtrack available
Spotify https://open.spotify.com/album..../4KqGdTFN3TdhSICvRuz
Apple Music https://music.apple.com/ca/alb....um/deep-blue-origina
AmazonHD (best-uncompressed sound) https://music.amazon.ca/albums..../B094DRFNR8?ref=dm_s

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In this tutorial we build a Sequence to Sequence (Seq2Seq) model from scratch and apply it to machine translation on a dataset with German to English sentences, specifically the Multi30k dataset. There was a lot of things to go through and explain so the video is a bit longer than my normal videos, but I really felt I wanted to share my thoughts, explanations and the details of the implementation!

Resources I used and read to learn about Seq2Seq:
https://github.com/bentrevett
https://arxiv.org/abs/1409.3215
https://pytorch.org/tutorials/....intermediate/seq2seq

Comment on resources:
I think bentrevett on Github is awesome and I was heavily inspired in this video by his Seq2Seq Tutorials and I really recommend checking him out, he puts out a lot of great tutorials on his Github.

People often ask what courses are great for getting into ML/DL and the two I started with is ML and DL specialization both by Andrew Ng. Below you'll find both affiliate and non-affiliate links if you want to check it out. The pricing for you is the same but a small commission goes back to the channel if you buy it through the affiliate link.
ML Course (affiliate): https://bit.ly/3qq20Sx
DL Specialization (affiliate): https://bit.ly/30npNrw
ML Course (no affiliate): https://bit.ly/3t8JqA9
DL Specialization (no affiliate): https://bit.ly/3t8JqA9

GitHub Repository:
https://github.com/aladdinpers....son/Machine-Learning

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PyTorch Playlist:
https://www.youtube.com/playli....st?list=PLhhyoLH6Ijf

OUTLINE:
0:00 - Introduction
1:27 - Imports
2:05 - Data processing using Torchtext
5:55 - Implementation of Encoder
11:02 - Implementation of Decoder
19:43 - Putting it togethor to Seq2Seq
27:57 - Setting up training of the network
41:03 - Fixing Errors
42:18 - Evaluation of the model
49:32 - Ending and Bleu score result

In this tutorial we build a Sequence to Sequence (Seq2Seq) with Attention model from scratch in Pytorch and apply it to machine translation on a dataset with German to English sentences, specifically the Multi30k dataset.

Resources to learn more:
https://github.com/bentrevett
https://youtu.be/SysgYptB198
https://youtu.be/quoGRI-1l0A
https://arxiv.org/abs/1409.0473
https://pytorch.org/tutorials/....intermediate/seq2seq

Comment on resources:
I think bentrevett on Github is awesome and this series of videos was heavily inspired in this video by his Seq2Seq Tutorials and I really recommend checking him out, he puts out a lot of great tutorials on his Github.

People often ask what courses are great for getting into ML/DL and the two I started with is ML and DL specialization both by Andrew Ng. Below you'll find both affiliate and non-affiliate links if you want to check it out. The pricing for you is the same but a small commission goes back to the channel if you buy it through the affiliate link.
ML Course (affiliate): https://bit.ly/3qq20Sx

DL Specialization (affiliate): https://bit.ly/30npNrw
ML Course (no affiliate): https://bit.ly/3t8JqA9
DL Specialization (no affiliate): https://bit.ly/3t8JqA9

GitHub Repository:
https://github.com/aladdinpers....son/Machine-Learning

✅ Equipment I use and recommend:
https://www.amazon.com/shop/aladdinpersson

❤️ Become a Channel Member:
https://www.youtube.com/channe....l/UCkzW5JSFwvKRjXABI

✅ One-Time Donations:
Paypal: https://bit.ly/3buoRYH
Ethereum: 0xc84008f43d2E0bC01d925CC35915CdE92c2e99dc

▶️ You Can Connect with me on:
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LinkedIn - https://www.linkedin.com/in/al....addin-persson-a95384
GitHub - https://github.com/aladdinpersson

PyTorch Playlist:
https://www.youtube.com/playli....st?list=PLhhyoLH6Ijf

Come check out my latest 4K Movie Review of this classic 90s slasher "I Know What You Did Last Summer" and find out if this release from Sony is worth your time and money!
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We were invited to Bulgaria by "Our Home is Bulgaria" to explore the country for the first time this year and it was an amazing experience to travel through this space with so much history and diverse landscapes. Some of the places we feature here are the Seven Rila Lakes, Alexander Nevsky Cathedral, Thracian Tomb of Kazanlak, Belogradchik Fortress, Devetashka cave, and Mount Buzludzha.

WARNING: To view at 8K 60P you will need to use Chrome, Opera, Firefox, or Edge.

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CGI 3D Animated Short Film: Sprite Fright Animated Short Film by Blender Studio. Featured on CGMeetup Gallery https://www.cgmeetup.com/gallery

Sprite Fright is a Animated slasher Horror Comedy and produced as the thirteenth Blender Foundation Open Movie. A group of rowdy, city-slicking teens set camp in a secluded part of the woods for their biology project.

Produced by Blender Studio. Made with Blender 3.0. Rated PG.
Get the production files, assets and exclusive making-of videos by joining Blender Studio at https://studio.blender.org/films/sprite-fright/ or https://www.blender.org

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CGI Animated Short Film HD: "Sprite Fright" by Blender Studio | CGMeetup
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#cgi #animation #animated #3d #shortfilm #short #animatedshortfilm

#bobbysimha #karunakaran #comedy #food #streetfood #tamilmovies #tamillatestmovies #tamilhdmovies #tamilnewmovies #tamiloldmovieshd
Aadama Jaichomada (transl. We won without playing) is a 2014 Tamil language black comedy film directed by Badri. Produced by B&C films and Upshot Films, co-produced by Skilite Creations, the film stars Karunakaran, Bobby Simha and Vijayalakshmi in prominent roles, while Balaji Venugopal, Aadukalam Naren, K. S. Ravikumar amongst others appear in supporting roles. The dialogues were written by actor Shiva.[1] The film deals with corruption involved in cricket.[2] Aadama Jaichomada was released on 19 September 2014.

Cast
Karunakaran as Panneer
Bobby Simha as Inspector Bhoominathan
Vijayalakshmi as Rama
Balaji Venugopal as Dhayalan
K. S. Ravikumar as Police Commissioner
Aadukalam Naren as Film Producer
Radha Ravi as Producer
Chetan as Constable Mariadas
For More HD Videos Subscribe
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この動画では、ニューラルネットワークの歴史を追いながらDeep Learningの基礎についてやさしく解説します。

前回の動画（今Deep Learningに取り組むべき理由）はこちらです。
https://www.youtube.com/watch?v=-Dl8s4iufxI

再生リスト「Deep Learning入門」
https://www.youtube.com/playli....st?list=PLg1wtJlhfh2

Neural Network Console
https://dl.sony.com/ja/

Neural Network Libraries
https://nnabla.org/ja/

How the brain works, according to Geoff Hinton.
Presented at the NIPS'2010 workshops banquet for the Deep Learning and Unsupervised Feature Learning workshop.

Realized by Yoshua Bengio with the help of Olivier Delalleau, and the complicity of Andrew Ng, Yann LeCun, Marc'Aurelio Ranzato, and Honglak Lee.

Learn more about CNNs → http://ibm.biz/cnn-guide
Learn more about Neural Networks → http://ibm.biz/neural-networks-guide
Check out IBM Watson Studio → http://ibm.biz/prod-ibm-watson-studio

Convolutional neural networks, or CNNs, are distinguished from other neural networks by their superior performance with image, speech, or audio signal inputs. But how exactly do they work?

In this lightboard video, Martin Keen with IBM, explains how this deep learning algorithm operates to enable machines to view the world as humans do.

Get started on IBM Cloud at no cost → http://ibm.biz/free-acct-creation
Subscribe to see more videos like this in the future → http://ibm.biz/subscribe-now​​

#ConvolutionalNeuralNetworks #Neural Networks #AI

GPT-3 is super intelligent NLP deep learning model. In order to understand GPT-3 or later version, we should understand fundamental basic of it, and this video is covering the basic of GPT which covers before the transformer, and summary of transformer and the basic fundamental of GPT by looking at GPT-1.