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Santiago

Apr 12, 2021 • 8 tweets • 4 min read • Read on X

If you are looking to get a background in math before starting with machine learning, here is all the material you need covering the following topics:

• Probabilities & Statistics
• Linear Algebra
• Multivariate Calculus

More than enough to get started.

↓ 1/7

Seeing Theory

seeing-theory.brown.edu

An interactive website that will take you through some of the most critical concepts of Probabilities and Statistics.

These will be enough to get you started, and you will have fun while going through it!

↓ 2/7

Statistics 110: Probability

youtube.com/playlist?list=…

If you are looking for more, this course from Harvard University is an excellent introduction to probability as a language and a set of tools for understanding statistics, science, risk, and randomness.

↓ 3/7

Essence of Linear Algebra

youtube.com/playlist?list=…

Who doesn't love Grant Sanderson's YouTube videos?

Go through this playlist for a refresher in Linear Algebra, and you'll be more than ready to face any machine learning demons.

↓ 4/7

Linear algebra

ocw.mit.edu/courses/mathem…

MIT Course 18.06.

Taught by Profesor Gilbert Strang, this is simply one of the best linear algebra courses that you'll ever find.

Prof. Gilbert makes the subject ridiculously simple and engaging.

↓ 5/7

Mathematics for Machine Learning: Multivariate Calculus

coursera.org/learn/multivar…

A free, beginner-friendly introductory course to building your confidence and introduce you to the multivariate calculus required to build many common machine learning techniques.

↓ 6/7

Essence of Calculus

youtube.com/playlist?list=…

This is Grant Sanderson's excellent take on calculus.

A series of interactive videos that are informative and make calculus feel like something that you could have discovered yourself.

↓ 7/7

@svpino

If you find these threads helpful, follow me @svpino for a weekly stream of machine learning content.

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Santiago

@svpino

Aug 12

The single most undervalued fact of linear algebra:

Matrices are graphs, and graphs are matrices.

Encoding matrices as graphs is a cheat code, making complex behavior simple to study.

Let me show you how!

By the way, this thread is courtesy of @TivadarDanka. He allowed me to republish it.

3 years ago, he started writing a book about the mathematics of Machine Learning.

It's the best book you'll ever read:

Nobody explains complex ideas like he does.tivadardanka.com/books/mathemat…

If you look at this example, you probably figured out the rule.

Each row is a node, and each element represents a directed and weighted edge. We omit any edges of zero elements.

The element in the 𝑖-th row and 𝑗-th column corresponds to an edge going from 𝑖 to 𝑗.

Read 18 tweets

Santiago

@svpino

Jul 12

A common fallacy:

If it's raining, the sidewalk is wet. But if the sidewalk is wet, is it raining?

Reversing the implication is called "affirming the consequent." We usually fall for this.

But surprisingly, it's not entirely wrong!

Let's explain it using Bayes Theorem:

1/10

This explanation is courtesy of @TivadarDanka. He allowed me to republish it.

He is writing a book about the mathematics of Machine Learning. It's the best book I've read:

Nobody explains complex ideas like he does.

2/10tivadardanka.com/books/mathemat…

We call propositions of the form "if A, then B" implications.

We write them as "A → B," and they form the bulk of our scientific knowledge.

For example:

"If X is a closed system, then the entropy of X cannot decrease" is the second law of thermodynamics.

3/10

Read 10 tweets

Santiago

@svpino

Jun 12

Some of the skills you need to start building AI applications:

• Python and SQL
• Transformer and diffusion models
• LLMs and fine-tuning
• Retrieval Augmented Generation
• Vector databases

Here is one of the most comprehensive programs that you'll find online:

"Generative AI for Software Developers" is a 4-month online course.

It's a 5 to 10-hour weekly commitment, but you can dedicate as much time as you want to finish early.

Here is the link to the program:

I also have a PDF with the syllabus:bit.ly/4aNOJdy

I'm a huge fan of online education, but most of it is all over the place and mostly theoretical.

This program is different:

You'll work on 4 different hands-on projects. You'll learn practical skills you can use at the office right away.cdn.sanity.io/files/tlr8oxjg…

Read 6 tweets

Santiago

@svpino

Jun 10

There's a stunning, simple explanation behind matrix multiplication.

This is the first time this clicked on my brain, and it will be the best thing you read all week.

Here is a breakdown of the most crucial idea behind modern machine learning:

1/15

This explanation is courtesy of @TivadarDanka. He allowed me to republish it

3 years ago, he started writing a book about the mathematics of Machine Learning.

It's the best book you'll ever read:

Nobody explains complex ideas like he does.

2/15tivadardanka.com/books/mathemat…

Let's start with the raw definition of the product of A and B.

This looks horrible and complicated.

Let's unwrap it step by step.

3/15

Read 15 tweets

Santiago

@svpino

May 28

This assistant has 169 lines of code:

• Gemini Flash
• OpenAI Whisper
• OpenAI TTS API
• OpenCV

GPT-4o is slower than Flash, more expensive, chatty, and very stubborn (it doesn't like to stick to my prompts).

Next week, I'll post a step-by-step video on how to build this.

The first request takes longer (warming up), but things work faster from that point.

Few opportunities to improve this:

1. Stream answers from the model (instead of waiting for the full answer.)

2. Add the ability to interrupt the assistant.

3. Whisper running on GPU

Unfortunately, no local modal supports text+images (as far as I know,) so I'm stuck running online models.

The TTS API (synthesizing text to audio) can also be replaced by a local version. I tried, but the available voices suck (too robotic), so I kept OpenAI's.

Read 4 tweets

Santiago

@svpino

May 25

I’m so sorry about anyone who bought the rabbit r1.

It’s not just that the product is non-functional (as we learned from all the reviews), the real problem is that the whole thing seems to be a lie.

None of what they pitched exists or functions the way they said.

They sold the world on a Large Action Model (LAM), an intelligent AI model that would understand applications and execute the actions requested by the user.

In reality, they are using Playwright, a web automation tool.

No AI. Just dumb, click-around, hard-coded scripts.

Their foundational AI model is just ChatGPT + scripts.

Rabbit’s founder lied on their marketing videos, during interviews, when he presented the product, and lied on Discord when answering questions from early supporters.

And that’s just the beginning:

Read 4 tweets

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