This video is about the Discrete Fourier Transform.

Grokking Machine Learning Book:
https://www.manning.com/books/....grokking-machine-lea
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00:00 Introduction
00:58 The Discrete Fourier Transform
06:08 The Inverse Discrete Fourier Transform
09:11 The Formula
14:23 Matrix Form
15:45 Next Steps

Latent Dirichlet Allocation is a powerful machine learning technique used to sort documents by topic. Learn all about it in this video!

This is part 1 of a 2 video series.
Video 2: https://www.youtube.com/watch?v=BaM1uiCpj_E

For information on my book "Grokking Machine Learning": https://www.manning.com/books/....grokking-machine-lea
Discount code (40%): serranoyt

0:00 Introduction
0:11 The problem
3:47 Machine that generates documents
5:13 Blueprint for the LDA machine
5:49 Probability of a document
9:22 Quiz: Which one for topics?
11:06 A distribution of distributions
11:30 More topics? More dimensions
12:20 In More dimensions
12:55 Quiz: Where to put the topics?
14:05 Two Dirichlet distributions
14:22 Latent Dirichlet Allocation
22:05 Best settings on the machine
22:37 The winning arrangements
25:28 Series of two videos
25:48 Acknowledgements
26:30 Thank you!

Announcement: New Book by Luis Serrano! Grokking Machine Learning. bit.ly/grokkingML
40% discount code: serranoyt

A conceptual description of principal component analysis, including:
- variance and covariance
- eigenvectors and eigenvalues
- applications
As usual, very little formulas, lots and lots of pictures!

0:00 Introduction
0:46 Taking a picture
1:13 Dimensionality Reduction
2:02 Housing Data
5:09 Mean
7:46 Variance?
12:47 Covariance matrix
13:58 Linear Transformations
18:12 Eigenstuff
19:16 Eigenvalues
19:53 Eigenvectors
20:51 Principal Component Analysis (PCA)
26:05 Thank you!

This video is about the Fast Fourier Transform.

This is the third in a series of videos about Fourier transforms.

- First video: The Discrete Fourier Transform https://www.youtube.com/watch?v=T8XZxR5H04E
- Second video: Detecting Periodicity with the DFT https://youtu.be/bk9VGJNzQM0
- Third video: The Fast Fourier Transform (this one)

Grokking Machine Learning Book:
https://www.manning.com/books/....grokking-machine-lea
40% discount promo code: serranoyt

00:00 Introduction
00:27 The Discrete Fourier Transform
03:01 The Fast Fourier Transform
07:28 The Butterfly

Direct Preference Optimization (DPO) is a method used for training Large Language Models (LLMs). DPO is a direct way to train the LLM without the need for reinforcement learning, which makes it more effective and more efficient.
Learn about it in this simple video!

This is the third one in a series of 4 videos dedicated to the reinforcement learning methods used for training LLMs.

Full Playlist: https://www.youtube.com/playli....st?list=PLs8w1Cdi-zv

Video 0 (Optional): Introduction to deep reinforcement learning https://www.youtube.com/watch?v=SgC6AZss478
Video 1: Proximal Policy Optimization https://www.youtube.com/watch?v=TjHH_--7l8g
Video 2: Reinforcement Learning with Human Feedback https://www.youtube.com/watch?v=Z_JUqJBpVOk
Video 3 (This one!): Deterministic Policy Optimization

00:00 Introduction
01:08 RLHF vs DPO
07:19 The Bradley-Terry Model
11:25 KL Divergence
16:32 The Loss Function
14:36 Conclusion

Get the Grokking Machine Learning book!
https://manning.com/books/grok....king-machine-learnin
Discount code (40%): serranoyt
(Use the discount code on checkout)

Check out the latest (and most visual) video on this topic! The Celestial Mechanics of Attention Mechanisms: https://www.youtube.com/watch?v=RFdb2rKAqFw

This is the second of a series of 3 videos where we demystify Transformer models and explain them with visuals and friendly examples.

Video 1: The attention mechanism in high level https://youtu.be/OxCpWwDCDFQ
Video 2: The attention mechanism with math (this one)
Video 3: Transformer models https://www.youtube.com/watch?v=qaWMOYf4ri8

If you like this material, check out LLM University from Cohere!
https://llm.university

00:00 Introduction
01:18 Recap: Embeddings and Context
04:46 Similarity
11:09 Attention
20:46 The Keys and Queries Matrices
25:02 The Values Matrix
28:41 Self and Multi-head attention
33:54: Conclusion

In this video, we see two math problems that require the exact same logic to solve. However, one is very easy and one is very hard. Why?

For information on my book "Grokking Machine Learning":
https://www.manning.com/books/....grokking-machine-lea
Discount code (40%): serranoyt

Reinforcement Learning with Human Feedback (RLHF) is a method used for training Large Language Models (LLMs). In the heart of RLHF lies a very powerful reinforcement learning method called Proximal Policy Optimization. Learn about it in this simple video!

This is the first one in a series of 3 videos dedicated to the reinforcement learning methods used for training LLMs.

Full Playlist: https://www.youtube.com/playli....st?list=PLs8w1Cdi-zv

Video 0 (Optional): Introduction to deep reinforcement learning https://www.youtube.com/watch?v=SgC6AZss478
Video 1 (This one): Proximal Policy Optimization
Video 2: Reinforcement Learning with Human Feedback https://www.youtube.com/watch?v=Z_JUqJBpVOk
Video 3 (Coming soon!): Deterministic Policy Optimization

00:00 Introduction
01:25 Gridworld
03:10 States and Action
04:01 Values
07:30 Policy
09:39 Neural Networks
16:14 Training the value neural network (Gain)
22:50 Training the policy neural network (Surrogate Objective Function)
33:38 Clipping the surrogate objective function
36:49 Summary

Get the Grokking Machine Learning book!
https://manning.com/books/grok....king-machine-learnin
Discount code (40%): serranoyt
(Use the discount code on checkout)

Come join us in this Live Q/A where our guest is Miguel Otero Pedrido, the creator of Neural Maze!
Feel free to post your questions beforehand or ask them live!

Announcement: New Book by Luis Serrano! Grokking Machine Learning. bit.ly/grokkingML
40% discount code: serranoyt

A friendly explanation of how computer recognize images, based on Convolutional Neural Networks.
All the math required is knowing how to add and subtract 1's. (Bonus if you know calculus, but not needed.)
For a brush up on Neural Networks, check out this video: https://www.youtube.com/watch?v=BR9h47Jtqyw

For a code implementation, check out this repo:
https://github.com/luisguiserr....ano/manning/tree/mas

0:00 Introduction
0:22 Simple World
1:05 Keyboard
1:33 Image recognition software
4:39 Image Recognition Classifier
6:12 Artificial Intelligence
8:47 Gradient Descent
10:26 Slightly More Complex World
11:47 Previous Knowledge
24:27 Convolutional Neural Network
28:27 Advanced World

Announcement: New Book by Luis Serrano! Grokking Machine Learning. bit.ly/grokkingML
40% discount code: serranoyt

A visual description of Bayes' Theorem and the Naive Bayes algorithm, and an application to spam detection.
No previous knowledge is needed, aside from knowing how to multiply and divide, a visual mind and a desire to learn.

For a code implementation, check out this repo:
https://github.com/luisguiserr....ano/manning/tree/mas

0:00 Introduction
0:39 Spam Detector
4:59 Problem
10:34 Naive Bayes Classifier
17:00 Bayes Theorem

In this video, we learn about quantum superposition using the quantum glove experiment. In this thought experiment, the states of a qubit are represented by the color and the orientation of a glove. Using different measurements, the color of this glove can change by only observing it!

Announcement: New Book by Luis Serrano! Grokking Machine Learning. bit.ly/grokkingML
40% discount code: serranoyt

A friendly introduction to Bayes Theorem and Hidden Markov Models, with simple examples. No background knowledge needed, except basic probability.
Accompanying notebook:
https://github.com/luisguiserrano/hmm

In this live session we'll read and discuss two papers:
The illusion of thinking - by Apple
The illusion of the illusion of thinking - by Anthropic
Come join for a fun chat!

This is the first of a series of two videos on AI Agents.
In here, we talk about the strengths and weaknesses of LLMs, focusing on a specific example: Why are LLMs unable to tell good jokes, yet they can write such good poems?
This sets the tone for the next video on AI Agents.

Second video - Agents, Reasoning Models, and RAG: https://www.youtube.com/watch?v=xXL0gMo9Lso

Check out the latest (and most visual) video on this topic! The Celestial Mechanics of Attention Mechanisms: https://www.youtube.com/watch?v=RFdb2rKAqFw

This is the last of a series of 3 videos where we demystify Transformer models and explain them with visuals and friendly examples.

Video 1: The attention mechanism in high level https://www.youtube.com/watch?v=OxCpWwDCDFQ

Video 2: The attention mechanism with math https://www.youtube.com/watch?v=UPtG_38Oq8o

Video 3 (This one): Transformer models

If you like this material, check out LLM University from Cohere!
https://llm.university

Get the Grokking Machine Learning book!
https://manning.com/books/grok....king-machine-learnin
Discount code (40%): serranoyt
(Use the discount code on checkout)

00:00 Introduction
01:50 What is a transformer?
04:35 Generating one word at a time
08:59 Sentiment Analysis
13:05 Neural Networks
18:18 Tokenization
19:12 Embeddings
25:06 Positional encoding
27:54 Attention
32:29 Softmax
35:48 Architecture of a Transformer
39:00 Fine-tuning
42:20 Conclusion