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

New video:
https://youtu.be/IZtv9s_Wx9I

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

Reason for update:
I felt the video explanations could be clearer and better video quality. What I've done now is expand it into a new GAN playlist where DCGAN is one of those! Do check out the links above.

In this video we implement a generative adversarial network (GAN) in Pytorch. Specifically we're implementing a DCGAN (Deep Convolutional Generative Adversarial Network) trained on the MNIST-dataset to generate new digits.

✅ Support My Channel Through Patreon:
https://www.patreon.com/aladdinpersson

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

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

Papers to gain better understanding of GANs:
https://arxiv.org/abs/1406.2661 (Original GAN paper)
https://arxiv.org/abs/1511.06434 (DCGAN paper)
https://arxiv.org/abs/1606.03498 (Techniques for training GANs)

OUTLINE:
0:00 - Introduction
0:46 - Overview of the idea behind GANs
1:42 - Original GAN paper overview
4:27 - DCGAN paper overview
7:13 - Implementation of the Discriminator
12:43 - Implementation of the Generator
17:21 - Initialization of the network, dataset and hyperparameters
24:00 - Setting up the training phase
38:10 - Training the Network and visualizing results

Machine Learning Specialization: https://bit.ly/3UzcejB

I recently completed the machine learning specialization by Andrew Ng that replaces the original legendary machine learning course now with updated coding assignments in Python and improved lecture quality. In this video I share my thoughts on the specialization, who it's designed for and what you'll learn if you decide to take it.

Timestamps:
0:00 - Introduction
0:41 - Why this specialization?
2:03 - Thoughts on the instructor Andrew Ng
2:50 - Overall rating
3:10 - Who is it for?
4:06 - Overview of the courses
7:40 - Course structure
10:35 - Thoughts on what can be improved
14:48 - More detailed content walkthrough
19:58 - Time to complete
20:30 - Cost
21:10 - Summary of the specialization

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 Vigenere cipher also if you have any questions about this algorithm.

Article reviewed in video: https://sebastianraschka.com/b....log/2022/batch-size-

In this video I will show you how to create an input pipeline when dealing with text. We focus on TextLineDataset which is a quite general method that you can adapt to many different text data structure. In the tutorial I show you mainly demonstrating how to load the imdb dataset from a text file but I also try and give you some ideas and what to do if you're dealing with text data is differently structured, like split over multiple text files or a translation dataset split over two text files.

Download the data (IMDB) used in the video here:
https://www.kaggle.com/dataset..../ff33c576e11e20d0c3a

I learned a lot and was inspired to make these TensorFlow videos by the TensorFlow Specialization on Coursera. Below you'll find both affiliate and non-affiliate links, the pricing for you is the same but a small commission goes back to the channel if you buy it through the affiliate link.
affiliate: https://bit.ly/3t3tgI5
non-affiliate: https://bit.ly/3kZgN5B

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

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

OUTLINE:
0:00 - Introduction and Dataset Overview
1:39 - Load using TextLineDataset
4:13 - Filtering Dataset
8:12 - Creating Vocabulary
13:43 - Numericalizing with TokenTextEncoder
18:10 - Applying map on datasets
20:35 - Simple Model
22:30 - Dataset in Several Files
25:50 - Sketch Load Translation Dataset
29:22 - Ending

In this video we go through backward propagation calculations for a feedforward- neural network!

In this first video we go through the necessary notation in order to make the mathematical calculations for the forward as well as the backward propagation.

As I said in the video if you have never heard of neural networks before but still want to learn and wonder where to start to gain some understanding and intuition here is a great place:

https://www.youtube.com/watch?v=aircAruvnKk

3blue1brown has more videos of neural networks that I also recommend you to watch!

- Dino

Explanation and implementation of interval scheduling problem using a greedy algorithm.
CODE REPOSITORY: https://github.com/AladdinPerz....on/Algorithms-Collec

In this video I explain how Word2Vec works and it's two model variants in Continuous Bag of words (CBOW) and Skip-Gram. I also give an intuitive understanding of what embeddings are, why they are important as this is fundamentally what this algorithm is trying to learn.

Timestamps:
0:00 - Introduction to Word2vec
0:54 - Understanding Embeddings
5:20 - CBOW model of Word2Vec
8:46 - Skip-Gram model of Word2Vec
9:34 - Outro