Santiago Profile picture
27 Dec, 6 tweets, 1 min read
I've worked with Dell, HP, IBM, Cisco, HSBC, Disney, G4S, among other large companies.

Don't think for a minute that they have things figured out.

They have amazing development teams. They also have mediocre and straight-horrible teams.

🧵👇
[2] In my experience, smaller companies tend to be more selective when hiring: they can't afford to make a mistake.

I've found out that these smaller companies build consistently decent teams. (Although they have a harder time hiring talent.)

👇
[3] Larger companies, on the other hand, build teams across many different departments. Maintaining consistency is hard, if not impossible.

I met excellent teams: sharp, organized, building excellent products using state-of-the-art technology.

👇
[4] But other of their teams didn't have the same organization or sharp skills. Some of them were mind-blowing bad teams.

Same company, same goals, same compensation.

👇
[5] The moral of the story is that any developer can have a positive impact anywhere.

Don't be intimidated because a company "has everything figured it out." Chances are they don't.

👇
[6] The things you know today aren't obvious to everyone out there.

This is especially true in tech, where we live inside our echo chambers depending on where we work and who we hang out with.

Chase the job you want, and never limit your options before trying out.

• • •

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More from @svpino

28 Dec
I told everyone that I didn't care.

"Screw math! I've never been great with it, so I'm not starting with machine learning to fail at the end."

That was many years ago.

Math is still hard, but I don't think you should be scared at all. Here is why: 🧵👇
[1] One thing changed my mind: school pushed me to the deep end of the pool, and I was forced to swim.

I had to face my fears, and I started machine learning and realized that the math involved is not as scary (or as much) as some people believe.

👇
[2] Probably one of the most frequent questions I get is around the math needed for machine learning.

Answer:

▫️ Probabilities and Statistics
▫️ Linear Algebra
▫️ Calculus

But it turns out that this is not helpful.

👇
Read 18 tweets
27 Dec
An introduction to one of the the most basic structures used in machine learning: a tensor.

🧵👇
Tensors are the data structure used by machine learning systems, and getting to know them is an essential skill you should build early on.

A tensor is a container for numerical data. It is the way we store the information that we'll use within our system.

(2 / 16)
Three primary attributes define a tensor:

▫️ Its rank
▫️ Its shape
▫️ Its data type

(3 / 16)
Read 16 tweets
26 Dec
11 key concepts of Machine Learning.

— Supervised Learning Edition —

🧵👇
😜

Before starting, remember that, if you follow me, one of your enemies will be immediately destroyed (and you'll get to read more of these threads, of course.)

And if you don't follow me, well, you just hurt my feelings.

😜
1. Labels

(Also referred to as "y")

The label is the piece of information that we are predicting.

For example:

- the animal that's shown in a picture
- the price of a house
- whether a message is spam or not

👇
Read 13 tweets
22 Dec
The 8-step quick-start guide to learn Machine Learning.

🧵👇
1⃣ Start with Python 🐍

Yes, you can do other languages, but Python is by far the most straightforward option.

👇
2⃣ Get familiar with numpy, pandas, and matplotlib

These three libraries are probably the most common Python libraries you'll have to use every day.

(Even if you don't end up doing machine learning, these libraries are awesome and useful.)

👇
Read 10 tweets
21 Dec
Rumors are going around that Twitter cripples tweets that include links.

There's nothing in their official documentation, but a lot of people think that's the case.

I thought this through, and I will not play along.

🧵👇
Allegedly, if I disable the links, my tweets will get much more impressions because Twitter will push them to more people.

Assuming this is the case, what's the cost?

My followers will have to start copying, then pasting any links that I post.

(2 / 4)
Seems like a small nuance, but reading comments on tweets with disabled links, the process is very error-prone and a lot of people have trouble accessing the content.

This is not what I want.

(3 / 4)
Read 4 tweets
3 Dec
Transitioning from Software Engineering to Machine Learning.

🧵👇
I'll tell you my story.

It might work for you. It might not.

Hopefully, it gives you another perspective. Hopefully, it helps.

(2 / 14)
Many people see "Software Engineering" and "Machine Learning Engineering" as two completely different specialization areas.

There are many differences, for sure.

But I personally like to think about them as a single, fluid, all-encompassing position.

(3 / 14)
Read 14 tweets

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