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Santiago Profile picture
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11 Mar, 5 tweets, 2 min read
"Do I need a Ph.D. or a Master's degree to work as a machine learning engineer?"

No.

A lot of companies ask for degrees to weed out people that apply to jobs prematurely.

If you have the required skills and show your experience, the degree will not matter.
Both are valid paths and it will come down to your personal preference or what you need to accomplish

If you aren’t sure, online courses give you less risk upfront.
There are specific positions that do require (and will continue to do so) a degree in a related field.

But the industry has changed in the last few years. Fewer places require degrees anymore, and the tendency will continue in that direction.

Experience is the most important indicator of future performance.

Both professional and relevant personal experience count.

There are several ways you can go about this:

▫️ Contribute to Open Source projects
▫️ Get an internship
▫️ Freelance
▫️ Join Kaggle competitions
▫️ Build your own solutions for toy problems
▫️ Write a blog with what you've learned

• • •

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More from @svpino

Santiago Profile picture
11 Mar
Before you start building a machine learning model, you need a baseline.

I find it helpful to think about 3 different levels and tackle them in order.

Here is how I do this: ☕️🧵👇
▫️ Level 1: The human baseline

Before anything else happens, I find it useful to understand how humans do when solving the problem.

This gives me the ceiling that I should aspire to (or maybe even beat it, if I'm lucky!)
Sometimes, the human baseline will hint at whether a model is a feasible solution for the problem.

For example, if the data doesn't contain information that we can use to make predictions, humans will do very poorly. This will save us a lot of work!
Read 10 tweets
Santiago Profile picture
10 Mar
Let's talk a little bit about machine learning in the real world.

A seemingly simple classification problem that turns ugly quickly.

Hopefully, this gives you an idea of what it takes to put some of the pieces together.

Grab your ☕️, and let's do this thing!

🧵👇
Let's imagine a system where you could sell your stuff.

You submit a bunch of pictures of an object, and the system recommends a price range in which the object could be sold.

Let's focus on classifying the object from the pictures.
An image classification problem sounds simple enough. There are 1,000 examples out there!

Unfortunately, getting value from these systems requires a lot of considerations.

Let me throw a lot of ideas to you. This 🧵 is messy, just like a potential solution to the problem.
Read 19 tweets
Santiago Profile picture
9 Mar
Here is an underrated machine learning technique that will give you important information about your data and model.

Let's talk about learning curves.

Grab your ☕️ and let's do this thing!

🧵👇
Start by creating a model. Something simple. You are still exploring what works and what doesn't, so don't get fancy yet.
We are now going to plot the loss (model error) vs. the training dataset size. This will help us answer the following questions:

▫️ Do we need more data?
▫️ Do we have a bias problem?
▫️ Do we have a variance problem?
▫️ What's the ideal picture?
Read 16 tweets
Santiago Profile picture
8 Mar
This week, I'll be on Twitter Spaces with amazing company!

We'll be talking about some cool machine learning techniques. Each one of us, a different one.

Save the date, and you can join us from your mobile phone right from the Twitter application.
We are planning to record this session, but... But, we will be recording the screen of an iPhone and some other weird stuff to try and get the audio out.

Not the best process, but we will try to get clean audio out of this.
If everything works, @haltakov will make the audio available (likely in the form of a podcast.) Where and how are details that we'll share when we know.

If the audio comes out too crappy, we will probably not bother because it won't be useful for you anyway.
Read 6 tweets
Santiago Profile picture
7 Mar
Are you already using the walrus operator in Python 🐍? Image
Yup, I'm dumb and didn't realize this when I wrote it.

The good news is that the example still stands, but you are completely right: both lines inside the first loop should be swapped.

New things are always controversial.

People don't like to use things that change the syntax of their code because "it becomes less readable." I know people that complain vehemently about slicing in Python.

I'd rather try to use the language as it is.

Read 4 tweets
Santiago Profile picture
6 Mar
I'm writing one story about machine learning every week.

My goal is to teach you something new. Something that makes you feel smarter. Something that helps you in your career.

The first issue is coming out this Friday, and I'd love to count on you!

👇 Image
You can subscribe here: digest.underfitted.io.

100% free.

And it will be a two-way street: reply to one of the emails, and I'll do my best to answer and package some of them in future issues.

The content that I've always wanted to read but never found.
Give it a try and, after reading a couple of issues, decide whether you feel better by reading them or not.

The good news is that it costs nothing to read them.

If I were you, I'd like it... but I'm also biased 😉

Read 4 tweets

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