Santiago Profile picture
21 Feb, 8 tweets, 2 min read
Go to college. Send your kids. Celebrate those that make it happen.

College is a good thing. If you can afford it, do it.

Most people telling you that college sucks went to college. Most people that didn't go whish their kids would.

🧵👇
You won't replace college with YouTube videos, or reading books, or following tutorials.

Some people may. Most people won't.

Yes, the knowledge is all out there, but college is just not about learning new things.

👇
College doesn't guarantee you a job but look at the statistics of median income and unemployment among those that went and those that didn't.

The numbers should tell us something.

👇
One of the things we are working hard on in the U.S. is to make college more affordable for more people, not to get rid of it.

We want to send more people of color and from disfavored communities. We know that it will lift them! We know college brings prosperity.

👇
In tech, many people point out that you can learn to code without going to college.

This is as relevant as arguing that you can learn to paint without going to art school. Or that you play soccer but never went to a sports academy.

What's your point?
Life is full of extraordinary people. I've met extremely accomplished folks that dropped out after high school.

I'm very happy for them!

Bill Gates, Mark Zuckerberg, and Steve Jobs also dropped out. And...

Yeah, this another nonsense argument.

👇
College is not for everyone. Consider it, however, like something that will boost your chances.

It's done it for generations. It's still a good predictor of success.

And even if you don't go, wear a mask to beat this thing, and stay tuned for more!

🦕
(The thread got all messed up... probably because I'm an idiot and made a mistake when writing it.)

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More from @svpino

20 Feb
25 popular libraries and frameworks for building machine and deep learning applications.

Covering:

▫️ Data analysis and processing
▫️ Visualizations
▫️ Computer Vision
▫️ Natural Language Processing
▫️ Reinforcement Learning
▫️ Optimization

A mega-thread.

🐍 🧵👇
(1 / 25) TensorFlow

TensorFlow is an end-to-end platform for machine learning. It has a comprehensive, flexible ecosystem of tools and libraries to build and deploy machine learning-powered applications.
(2 / 25) Keras

Keras is a highly-productive deep learning interface running on top of TensorFlow. It provides essential abstractions and building blocks for developing and shipping machine learning solutions with high iteration velocity.
Read 20 tweets
19 Feb
I'm sad to watch many developers working 80-hour weeks to get one inch ahead of everyone else.

And yet, they are missing the biggest opportunity of their lives right under their noses.

🧵👇
Today, you don't leap ahead by learning another framework, watching another tutorial, or building another web page.

That's incremental improvement. Important, but not extraordinary.

👇
Hours don't mean anything, and everything you add to your portfolio will be obsolete in the next couple of years.

What's really going to move the needle is the impact of your work. It's how you change and influence those around you.

👇
Read 10 tweets
18 Feb
You gotta think about this one carefully!

Imagine you go to the doctor and get tested for a rare disease (only 1 in 10,000 people get it.)

The test is 99% effective in detecting both sick and healthy people.

Your test comes back positive.

Are you really sick? Explain below 👇
The most complete answer from every reply so far is from Dr. Lena. Thanks for taking the time and going through it!

You can get the answer using Bayes' theorem, but let's try to come up with it in a different —maybe more intuitive— way.

👇
Read 9 tweets
17 Feb
Imagine a model to predict customers who will unsubscribe from your service.

You want to incentivize them with $10 because they will cost you $100 if they churn.

Look at the attached confusion matrix showing that the model is only 77% accurate.

Is this model good enough?
I love this question because it puts a couple of things in perspective:

1. A model that doesn't look too good by the numbers.

2. A business case that can use a less-than-ideal solution to solve the problem.
There's only one question about this problem: how many people will not churn if they get the incentive?

We don't know, but we can play out different scenarios and see what happens.
Read 9 tweets
16 Feb
Imagine that you ask a yes/no question to 1,000 people, and each person answers correctly 51% of the time.

You count the different answers and pick the most common one.

How likely are you to end up with the correct answer?

🧵👇
Don't feel bad if you think it's 51% — We all did!

If every person answers independently from the rest, you'll end up with the correct answer ~75% of the time.

And if you ask 10,000 people, the chance of getting it right goes up to ~97%!

Mind-blowing, right?

(2 / 6)
If you care about the math behind this, take a look at the attached expression. (But it doesn't matter if you don't.)

This is what's important:

The law of large numbers ensures that we get more correct answers as we ask more people.

(3 / 6)
Read 7 tweets
15 Feb
I have not seen any proof that Twitter "kills your content" if you include links to your tweets.

Here is the result of a very unscientific experiment: comparing my top 10 tweets with and without links.

If you have something concrete, please let me know.
This is anecdotal evidence at best.

It doesn't prove that Twitter doesn't mess with your links, but it does suggest that —if anything is going on— it is much more subtle than what some believe.

I haven't found any documentation either.
This is what I do know:

Breaking the links that you add to your tweets is self-serving: it makes it worse for the people who follow you. They can't just click to get the content.

I can't see how this will make your content better in any way.
Read 4 tweets

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