Santiago Profile picture
19 Feb, 10 tweets, 2 min read
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.

πŸ§΅πŸ‘‡
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.

πŸ‘‡
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.

πŸ‘‡
You don't get extraordinary results by doing ordinary things, no matter how many of them you do.

You need to play a different game.

πŸ‘‡
Have you seen how much data we have collected about literally every single shit around us?

Think about this.

In 100 years, people will be able to look back and reproduce our world piece by piece.

Every. Single. Thing. is sitting today in a database somewhere.

πŸ‘‡
And this represents one of the most extraordinary opportunities for anyone paying attention.

We desperately need people that:

▫️ Process that data
▫️ Curate it
▫️ Capture more of it
▫️ Transform it
▫️ Expand it
▫️ Interpret it

We need people capable of understanding it!

πŸ‘‡
Where do you think the most extraordinary achievements in the next 50 years will come from?

I can definitely tell you that, whatever they are, they'll be fueled by the knowledge we have accumulated and our ability to get insights that drive change.

πŸ‘‡
Don't wait for somebody to give you permission.

The data is there, and now it's up to us to do something good with it.

The trick is to move from a tool-focused mindset to a value-driven one:

▫️ What can you do to tap into what's sitting in front of you?

πŸ‘‡
If you are a JavaScript developer or a mobile developer. If you build web pages or cloud applications. Whoever you are and whatever you do:

Data is the fuel that's changing humanity.

Don't miss it.

This is your ticket. This will set you apart.

πŸ‘‡
We can do this shit together!

Follow me, and every week I'll help you navigate this thing from doing it, failing at it, learning, and fixing it.

πŸ¦•

β€’ β€’ β€’

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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.

🐍 πŸ§΅πŸ‘‡
(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
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 πŸ‘‡
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 β€”maybe more intuitiveβ€” way.

πŸ‘‡
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?

πŸ§΅πŸ‘‡
Don't feel bad if you think it's 51% β€” 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 β€”if anything is going onβ€” 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
14 Feb
A collection of the most interesting threads I've written about machine learning.

🧡 x 🧡
Read 13 tweets

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