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Santiago

@svpino

Nov 12

This is worth 1,000+ hours of engineering work every year:

1. Reproducing a bug
2. Getting detailed debug data
3. Writing how to reproduce it
4. Putting it all together in a good bug report

This tool can do all of this and cut the time it takes to fix the bug by 70%+:

makes the reporting and fixing process really fast!

Click once, and engineers get:

• Console logs
• Network requests
• Timing waterfall
• Repro steps
• Session & user details
• Device & OS
• Backend logs

Check the attached video. Jam.dev

It's just a browser extension - so anyone can report bugs w/ technical details.

Even after the bug just happened!

You can click instant replay, and Jam will create a detailed report with real-time data and video up to the last 2 minutes.

Read 4 tweets

Santiago

@svpino

Oct 1

My new soon-to-be Linux laptop right before I start assembling it.

RAM and SSD are now installed. Took me 1 minute and I didn’t even read the manual.

The packaging is very nice. A lot of cardboard. This thing comes well protected.

Mostly, frustration-free packaging. Reminiscent of Apple’s boxes.

Read 13 tweets

Santiago

@svpino

Sep 16

How can you build a good understanding of math for machine learning?

Here is a complete roadmap for you.

In essence, three fields make this up:

• Calculus
• Linear algebra
• Probability theory

Let's take a quick look at them!

This thread is courtesy of @TivadarDanka.

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…

1. Linear algebra.

In machine learning, data is represented by vectors. Essentially, training a learning algorithm is finding more descriptive representations of data through a series of transformations.

Linear algebra is the study of vector spaces and their transformations.

Read 9 tweets

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

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