StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation

Course Materials: https://github.com/maziarraiss....i/Applied-Deep-Learn

In this video I explain LDA and go through a tutorial paper on how it works using collapsed gibbs sampling. The next video will be a implementation video :)

This method is an old school method and it's not clear how useful it is today, but a lot of course teach this topic so it must have some historical value I feel. It's one of Andrew Ng's most cited papers!

Paper tutorial: https://coli-saar.github.io/cl....19/materials/darling

Timestamps:
0:00 - Introduction
1:18 - What is topic modelling?
2:41 - LDA
13:30 - Posterior Inference
15:09 - Gibbs Sampling
18:06 - Collapsed Gibbs
21:50 - Finding conditional probability
26:48 - Implementation
30:08 - Pseudo code
32:25 - Ending

In this video we do a paper walk through of the GCN (Graph Convolutional Network) paper that is the most cited and one of the impactful in graph neural networks. We understand how they derived it and how it works in detail.

Big thanks to MakinaRocks for sponsoring this video, and I encourage you to check out Link which is a jupter lab extension they have developed to make notebooks more intuitive and easier to use. A few of the features I’ve found useful are:
1️⃣ Caching result from running cells in notebooks to avoid re-running them
2️⃣ Visualizing cell dependencies
3️⃣ Integrated version control

Check it out⬇️
https://bit.ly/3F4COvv

Link Demo Video 👉 https://youtu.be/uM2uPG-1eQQ
Link Documentation 👉https://makinarocks.gitbook.io/link/

Timestamps:
0:00 - Introduction
1:00 - Sponsored Segment: Link
2:09 - Abstract and overview
4:13 - Introduction to the problem
8:53 - How GCNs work
13:47 - Theory of GCN derivation
21:25 - GCN Node classification example
24:33 - Conclusions & Results
25:13 - Ending thoughts

#link #gcn

A quick look at CBOW and how it looks like it in code. I explained how this model works in the previous example so check that out before you look at this one to get a better understanding.

Timestamps:
0:00 - Introduction
0:48 - Imports
0:53 - CBOW model
5:10 - Example of how to train it
8:52 - Ending

How would you explain what machine learning is? In this video I try to explain it in varying degrees of specificity and how to answer the question depending on the person asking the question. I also go into what subcategories of machine learning exists, which we will also go deeper into in future videos.

Timestamps:
0:00 - Introduction
0:40 - What is Machine Learning?
1:36 - More specific explanation by Arthur Samuel
2:21 - Most specific definition
3:35 - Subcategories of ML
5:27 - Supervised Learning (vaguely explained)
5:47 - Unsupervised Learning (vaguely explained)
6:10 - Recommender Systems (vaguely explained)
6:30 - Reinforcement Learning (vaguely explained)
7:00 - Sub-Sub Categories: Self-Supervised Learning
7:40 - Sub-Sub Categories: Semi-Supervised Learning
8:32 - Ending

Hi, I made this video when a lot of students were questioning about preparing .csv file on Aladdin Persson's youtube in the following video.

How to build custom Datasets for Images in Pytorch
https://www.youtube.com/watch?v=ZoZHd0Zm3RY

In this video I go through how to code the Hill cipher in Python. I try to explain everything in simple terms, but this video was a bit challenging!

Github repository:
https://github.com/AladdinPerz....on/Algorithms-Collec

 Check out my previous video on the Hill cipher also if you have any questions about this algorithm.

I was inspired to make these videos by this specialization: https://bit.ly/3SqLuA6

A clean, simple and readable implementation of ESRGAN :)

In this video we code the K nearest neighbor (kNN) classifier from scratch in Python. We implement both the intuitive and a very efficient no-loop implementation!

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:
Twitter - https://twitter.com/aladdinpersson
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

I was inspired to make these videos by this specialization: https://bit.ly/3SqLuA6

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks: https://arxiv.org/abs/1809.00219

#PaperReview #PaperExplained

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:
Twitter - https://twitter.com/aladdinpersson
LinkedIn - https://www.linkedin.com/in/al....addin-persson-a95384
Github - https://github.com/aladdinpersson

GAN Playlist:
https://youtube.com/playlist?l....ist=PLhhyoLH6IjfwIp8

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

Timestamps:

Welcome to The ALT Code!

Kaggle image dataset used in the video: https://www.kaggle.com/c/carva....na-image-masking-cha

Aladdin Persson viedeo about UNET: https://youtu.be/oLvmLJkmXuc

In this video I build the UNET neural network architecture and use it for image segmentation in the Carvana Kaggle competition. Unfortunately, I couldn't train the model due to some tensorflow bugs, but I'll try to solve them and show you the result in an upcoming video. If you have any recommendation or advice leave it in the comments and I will gladly read it.

Video sections:
00:00 Intro
02:03 Start coding
04:25 Problems and bugs
05:24 Building nn architecture
09:24 More problems and bugs (same)

I hope you've liked the content. If so, remember to leave a like, comment and subscribe to the channel so you don't miss any video.
https://www.youtube.com/channe....l/UC-PxtaHoggfRI93H_



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In this video I walkthrough the basics of the Ceaser Cipher and in the next video we will code it in Python.

Link to Python tutorial: https://www.youtube.com/watch?v=6YBqtYkzzmY&t=17s

In this video I go through a simple cryptography algorithm in Python. I try to explain everything in simple terms and make it beginner friendly!



Github repository:
https://github.com/AladdinPerz....on/Algorithms-Collec


Check out my previous video on the Caesar cipher also if you have any questions about this algorithm.

Sharing my thoughts, experience and pros/cons with the specialization. In summary if you want a tldw it's good and worth taking. If you want more details look at the video ;) Support the channel by using affiliate link below with no additional cost for you

Course (affiliate):
https://bit.ly/3nCULaQ

Course (no affiliate):
https://www.coursera.org/speci....alizations/generativ