Santiago Profile picture
24 Jan, 23 tweets, 3 min read
Some of the things I've learned in more than 20 years in the tech industry.

You need to hear these.

๐Ÿงต๐Ÿ‘‡
Listen to more people who don't look like you, don't speak your language, and don't come from the same place you do.

We aren't doing this near enough.
Small habits compound.

No small improvement is too small.

Just aim for something new every day, and you'll be surprised at the end.
Take responsibility.

It doesn't really matter how you feel, I'm sure you could have done better.
Always keep the big picture in mind and never lose the forest for the trees.

Be the person that pulls everyone out of the rabbit holes.
Focus on the final goal, and don't worry too much about how you get there.

Great results will get you farther than processes, but good processes can help you achieve good results.
Be generous with your knowledge.

It's funny how everything you share finds a way to reward you back.
Who you are is more important than who you were.

We all make mistakes. Move on from them and focus on what's coming.
There are no stupid questions.

Ask away!

(There are, however, stupid people with fragile egos that get bothered when others ask. Ignore them.)
Change is the only thing you can always count on. (And death, and taxes, of course.)

Embrace change.
Better is not always best.

People fantasize about perfection, but perfectionism rarely wins.

Shipping more often will give you better odds than gilding the lily.
Learn to say no.

(I can't say this loud enough!)

Be gracious, professional, nice, but say it more.
Make a habit out of learning.

What you know today will be outdated tomorrow.

Make a plan to keep up and follow it... or you'll get behind.
Focus on one thing at a time.

Multi-tasking murders productivity.

(And turn your phone off!)
Job-hoping may be great for your bank account, but it does nothing to improve the impact you make in the world.

(And it looks horrible in your resume.)
Ideas are worth shit. Execution is worth everything.

Don't be the "idea person". Be the one that takes them and runs with them.
Good communication is a fundamental asset.

You can never invest too much in improving it.

(It doesn't matter how technically good you are if you can't properly communicate with others.)
The lack of diversity in the tech industry is real.

Inequality is real.

Stupid, entitled pricks that deny this are also real. Fuck them.
Always make sure you are solving the right problem.

It seems trivial, but you'll be surprised how much money is spent everyday walking in the wrong direction.
The best code is the one nobody wrote.

The best tool is the one you already have.

The best solution is usually the simplest one (and the one that solves the problem today.)
Nobody cares about the tools you know, the books you read, or the videos you watched.

Nobody cares about what your Twitter followers think.

People only care about the problems you can solve for them.
Assertiveness is the single most important skill you can build.
Follow me to learn more about machine learning, software engineering, and career advice for the tech industry.

And if you follow me, one of your enemies will die a painful death. And it is free ๐Ÿ˜‹!

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More from @svpino

26 Jan
11 short programming problems to stretch your imagination and make sure you are staying on your toes.

(Starting with the simple ones, they get more fun as you move towards the end.)

๐Ÿงต๐Ÿ‘‡
1. Write a function that reverses an array in place.

In other words, the function should not use an auxiliary array to do the work.
2. Write a function that finds the missing number in an unsorted array containing every one of the other 99 numbers ranging from 1 to 100.
Read 13 tweets
25 Jan
After well over a decade fully dedicated to web development, I learned a thing or two.

Here are a few thoughts that may be helpful:

๐Ÿงต๐Ÿ‘‡
Obviously, HTML, JavaScript, and CSS are table stakes.

There are plenty of jobs out there where you only require these, but it's always smart to go beyond the basics.

Don't get comfortable because the money is coming in.
A good way of increasing your value is by adventuring outside your comfort zone.

Whenever you are ready, I'd recommend you look into:

โ–ซ๏ธ Databases
โ–ซ๏ธ REST APIs
โ–ซ๏ธ UX

There's much more, but this is a great place to start.
Read 18 tweets
19 Jan
What are the differences between a multi-class classification problem and a multi-label classification problem?

(This is the answer to the second question from the attached thread.)



๐Ÿงต๐Ÿ‘‡
Let's assume we are classifying images into 3 different classes.

We will process each image and assign them to the class corresponding to the animal they show.

For example, we will classify the attached images as CAT, DOG, and CHICK.

๐Ÿ‘‡
Because we are classifying images into three or more classes, this is a multi-class classification problem.

The main characteristic of these problems is that the classes are mutually exclusive: we either classify an image as a CAT, DOG, or CHICK.

๐Ÿ‘‡
Read 8 tweets
18 Jan
100,000 followers!
Here is a rant about followers, some "you-can-do-it" encouragement, and a little bit about my account's story.

๐Ÿ‘‡
Of course, this tweet was a way for me to hack the number of people who go and look at my profile.

You know, one of those silly experiments I've been doing.

But here is the thing: although 100,000 is still out there, it will happen at some point this year!

๐Ÿ‘‡
Read 12 tweets
18 Jan
Why is it important to introduce non-linearities in a neural network?

The short answer: So we can solve more interesting problems.

The left image shows a classification problem that can be solved using a single dividing line. The image on the right is much more complex.

๐Ÿงต๐Ÿ‘‡
Here is a neural network with 2 hidden layers of 4 neurons. The activation is set to "Linear."

In just a few epochs, the network finds the correct solution.

Notice how the network uses a single dividing line in the output. That's all it can do with linear activations.

๐Ÿ‘‡
If we try the same network on the more complex problem, it will struggle to classify the data correctly.

We haven't introduced non-linearities in this network, so it won't find the proper solution for this type of problem.

๐Ÿ‘‡
Read 7 tweets
18 Jan
Here are the classes I took and the money I paid to get my Master's from Georgia Tech with a specialization in machine learning:

๐Ÿงต๐Ÿ‘‡
The classes:

1. Machine Learning
2. Computer Vision
3. Reinforcement Learning
4. Intro to Graduate Algorithms
5. Machine Learning for Trading
6. Database Systems Concepts and Design
7. Software Development Process
8. Software Architecture and Design

๐Ÿ‘‡
9. Human-Computer Interaction
10. Advanced Operating Systems
11. Software Analysis and Testing

You only need 30 credits to graduate. I completed 33.

It took me 4 years to go through all the classes (2015-2019). I was 35 when I started.

๐Ÿ‘‡
Read 6 tweets

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