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Santiago Profile picture
@svpino
Apr 12, 2021 • 8 tweets • 4 min read • Read on X
Scrolly
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
If you find these threads helpful, follow me @svpino for a weekly stream of machine learning content.

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More from @svpino

Santiago Profile picture
Apr 30
Improve your LLM-based applications by 200%:

Build an LLM-as-a-Judge evaluator and integrate it with your system.

This sounds harder than it is.

Here is how to do it and the things you need to keep in mind:

1/11 Image
(LLM-as-a-judge is one of the topics I teach in my cohort. The next iteration starts next week. You can join at .)

LLM-as-a-Judge is a technique that uses an LLM to evaluate the quality of the outputs from your application.

2/11ml.school
There are three specific scenarios you can test with a judge:

1. Choose the best of 2 answers (pairwise comparison)

2. Assess specific qualities of an answer (reference-free)

3. Evaluate the answer based on additional context (reference-based)

3/11 Image
Read 11 tweets
Santiago Profile picture
Apr 18
Falling off ladders to claim insurance checks is a multi-million-dollar fraud business in the US.

People bury insurance companies in paperwork to steal from them.

Enter RAG.

Here is how RAG is becoming the cheaters' worst nightmare (and how you can do the same):

1/8 Image
An insurance claim can easily have 20,000 pages, and somebody must read them all!

I work with @EyeLevel, and we built a fraud detection system using their GroundX platform.

Best RAG use case I've seen—and you can use GroundX to build your own in any vertical.

2/8
Here is how you stop the cheaters:

First, the application ingests all of the documentation. All 20,000+ pages go into the database.

GroundX uses a pretrained vision model to ingest and understand documents, which is especially good for complex documents.

3/8
Read 8 tweets
Santiago Profile picture
Mar 7
Here is an explanation of what MCP is, how it works, and why I think it's awesome.

I will also show you the MCP server I'm building.

This is good stuff.
For those who like YouTube better:



By the way, I won't like you anymore if you don't subscribe to my channel.
Here is where I'd start reading to understand what MCP is and what it does:



After you read "Core architecture", jump around all the other concepts. They will give you an idea of everything you can do with MCP. modelcontextprotocol.io/docs/concepts/…Image
Read 4 tweets
Santiago Profile picture
Jan 16
AWS is irrefutable proof that the right software with a great backend can succeed despite horrible UI/UX.
Craigslist: “hold my beer”
eBay: “Did anyone said ‘horrible UI’?”
Read 11 tweets
Santiago Profile picture
Nov 12, 2024
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 Profile picture
Oct 1, 2024
My new soon-to-be Linux laptop right before I start assembling it. Image
RAM and SSD are now installed. Took me 1 minute and I didn’t even read the manual. Image
The packaging is very nice. A lot of cardboard. This thing comes well protected.

Mostly, frustration-free packaging. Reminiscent of Apple’s boxes. Image
Read 13 tweets

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