In this video we go through how to implement a dynamic algorithm for solving the sequence alignment or edit distance problem. This is also referred to as the Needleman Wunsch algorithm, it seems as if this algorithm has quite many names :)

Code repository:

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

I recommend watching the explanation video before watching this implementation:

https://youtu.be/bQ7kRW6zo9Y

In this video we look at the datasets that are available to us through TensorFlow Datasets (tfds) and how we load them and then doing preprocessing, shuffling, batching, prefetching etc. For the example we load an image dataset (mnist) and a text dataset (imdb) and create simple models to do image classification and sentiment analysis.

New packages/imports we used in the video:
https://anaconda.org/conda-forge/matplotlib (pip install matplotlib)
https://anaconda.org/anaconda/tensorflow-datasets (pip install tensorflow_datasets)

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
0:16 - Keras vs TFDS vs tf.data
1:54 - Imports
2:38 - Image Loading with TFDS
12:59 - Text loading with TFDS
28:15 - Results and Ending

This is my solution to predict.m function in Programming assignment 3 from the famous Machine Learning course by Andrew Ng.

Github: https://github.com/AladdinPerz....on/Courses/tree/mast

Explanation step by step of how the sequence alignment algorithms problem works. Other common names of this algorithm is the Needleman Wunsch algorithm. In the next video we will code this algorithm from scratch using Python. On Leetcode this algorithm can be found under "Edit Distance", it seems this algorithm has many different names!

Code Repository:

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

In this tutorial we go through how an image captioning system works and implement one from scratch. Specifically we're looking at the caption dataset Flickr8k. There are multiple ways to improve the model: train a larger model (the one used is relatively small), train for longer and improve the model by adding attention similar to this paper: https://arxiv.org/abs/1502.03044.

Video of dataset (link in that video description to download the dataset yourself):
https://youtu.be/9sHcLvVXsns

✅ 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

I stole the thumbnail image from Yunjeys Github on Image Captioning which I also used as a resource. The implementation in the video differs a bit, but it's definitely worth checking out:
https://github.com/yunjey/pytorch-tutorial


OUTLINE:
0:00 - Introduction
0:12 - Explanation of Image Captioning
05:15 - Overview of the code
06:07 - Implementation of CNN and RNN
20:03 - Setting up the training
30:36 - Fixing errors
32:18 - Small evaluation and ending

#shorts #machinelearning #deeplearning #gnn #graphs

Tensors are super important for neural networks, but can be confusing because different people use the word "Tensor" differently. In this StatQuest, we clear this up and tell you what the big deal is. BAM!

NOTE: If you are not already familiar with Neural Networks, check out the Neural Network playlist: https://www.youtube.com/watch?v=CqOfi41LfDw&list=PLblh5JKOoLUIxGDQs4LFFD--41Vzf-ME1

For a complete index of all the StatQuest videos, check out...
https://app.learney.me/maps/StatQuest
...or...
https://statquest.org/video-index/

If you'd like to support StatQuest, please consider...

Buying my book, The StatQuest Illustrated Guide to Machine Learning:
PDF - https://statquest.gumroad.com/l/wvtmc
Paperback - https://www.amazon.com/dp/B09ZCKR4H6
Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC

Patreon: https://www.patreon.com/statquest
...or...
YouTube Membership: https://www.youtube.com/channe....l/UCtYLUTtgS3k1Fg4y5

...a cool StatQuest t-shirt or sweatshirt:
https://shop.spreadshirt.com/s....tatquest-with-josh-s

...buying one or two of my songs (or go large and get a whole album!)
https://joshuastarmer.bandcamp.com/

...or just donating to StatQuest!
https://www.paypal.me/statquest

Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter:
https://twitter.com/joshuastarmer

0:00 Awesome song and introduction
1:34 Why we need Tensors
4:52 Tensors store data
6:51 Tensors have hardware acceleration
7:37 Tensors have automatic differentiation

#StatQuest #Tensors #NeuralNetworks

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:
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

This is the Programming assignment 1 from Andrew Ngs Machine Learning course.

Github: https://github.com/AladdinPerz....on/Courses/tree/mast

In this video I show you how to to load different file formats (json, csv, tsv) in Pytorch Torchtext using Fields, TabularDataset, BucketIterator to do all the heavy preprocessing for NLP tasks, such as numericalizing, padding, building vocabulary, which saves us a lot of time to focus on actually training the models! In this example I show a toy example dataset for sentiment analysis but the things we go through are general and can be adapted for any dataset.

Resources I used to learn about torchtext:
https://torchtext.readthedocs.io/en/latest/
https://anie.me/On-Torchtext/
https://github.com/bentrevett
https://towardsdatascience.com..../how-to-use-torchtex
https://mlexplained.com/2018/0....2/08/a-comprehensive

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

In this video I walk through the basics of the Hill cipher!

Link to Python implementation: https://www.youtube.com/watch?v=xUEqlzqxSMQ

Paper: https://arxiv.org/abs/2003.08934

Full title: NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis

Timestamps:
0:00 - Introduction
0:54 - Goal of NeRFs
2:36 - NeRF network architecture
4:35 - The key idea you need to understand
6:17 - How NeRFs learn and work
12:15 - Intuition behind volume rendering
15:15 - Loss function
15:55 - Trick #1: Positional Encoding
17:36 - Trick #2: Hierarchical sampling
19:35 - Ending

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

Image-to-Image Translation with Conditional Adversarial Networks: https://arxiv.org/abs/1611.07004

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

✅ 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

#PaperReview #PaperExplained

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

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

Timestamps:
0:00 - Introduction
1:29 - Overview of paper
2:25 - Why GANs for Pix2Pix
3:16 - Loss Function
5:12 - Generator Architecture
9:24 - Discriminator Architecture
12:00 - Some training details
13:24 - Turkers to evaluate GANs
14:10 - Patch size for Discriminator
15:19 - Generator works for larger images
15:50 - More details for implementation
19:05 - Ending

This is my solution to predictOneVsAll.m function in Programming assignment 3 from the famous Machine Learning course by Andrew Ng.

Github: https://github.com/AladdinPerz....on/Courses/tree/mast

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

Full title: Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
Paper link: https://arxiv.org/abs/1703.10593

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

Timestamps:
0:00 - Introduction
1:06 - Sneak peak
2:00 - Problem statement
4:30 - Training setup & Cycle Consistency
7:16 - Loss
9:20 - Network architecture
13:15 - Identity loss
14:44 - Limitations of CycleGAN
16:08 - Implementation details
19:10 - Ending

Lista:

Arxiv Insights
bycloud
Daniel Bourke
DeepMind
OpenAI
facebook ai
PyTorch
PyTorch Lightning
Roboflow
Two Minute Papers
What's AI
Yannic Kilcher
3Blue1Brown
CodeEmporium
DeepLearning.TV
deeplizard
henry ai
Jeremy Howard
Jabrils
Karol Majek

Neural Networks and Deep Learning
Artificial Intelligence - All in One
Data Science Dojo
Machine Learning Study Groups
ML in PL
MIT OpenCourseWare
the Artificial Intelligence Channel
Yang Xu
ML Explained - Aggregate Intellect - AI.SCIENCE
Jordan Harrod
DeepMind
Machine Learning Street Talk
wasspPL
Aladdin Persson
Abhishek Thakur