Santiago Profile picture
30 Apr, 10 tweets, 2 min read
We've all heard the horror stories.

Are you ready for machine learning math? Are you sure you can download a library, go through a course and make things happen?

This is some unsolicited advice.

↓ 1/10
Back then, we had to write custom training loops. Every time.

We all heard horror stories about the complexity of statistics and how ugly linear algebra was. This was a real thing.

The barrier to start with machine learning was high and full of thorns.

↓ 2/10
Today, things are different.

The lack of programming skills is a much bigger hurdle than not understanding how derivatives work.

Wanna have a better chance? Learn to code today. Worry about math tomorrow.

↓ 3/10
A couple of days ago, a friend and I reflected on how far he's gotten and how many problems he's solved.

He was scared to start.

He thought he needed to take a year and eat as many complex formulas as possible.

Nonsense.

↓ 4/10
We have been building frameworks and libraries for years now to knock down the gates.

Much of the work today is using high-level code that abstracts away a lot of the complexity.

This doesn't solve all the problems. But it reduces them significantly.

↓ 5/10
Many people believe that you either understand how protons move in a wire or have no business changing an outlet.

That's fine. I don't need them to believe otherwise.

But I'm here to tell you that this is not true.

↓ 6/10
And to make sure we are both on the same page:

Math is important. I have no questions about it.

But how much of it you need and when exactly you need it is debatable and depends on the work you need to do.

↓ 7/10
I have two recommendations for you:

First, give machine learning a try.

Don't worry for now about the things *you think* you'll need. The time will come, and you can cross that bridge at that point.

↓ 8/10
Second, I just sent my newsletter with a more thoughtful article that you should read.

What you'll get:

1. Math resource recommendations.
2. When and how you should learn it.
3. A little bit more encouragement.

digest.underfitted.io/archive/586995

↓ 9/10
Let me send you on your way with three more things:

• Don't put it out anymore. Start.
• Follow me if you need more encouragement.
• I'm really persistent. I promise.

We can do this together.

10/10

• • •

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More from @svpino

1 May
A little over 12 years ago, the police started building a case against me.

That was stressful. They were watching. They wanted to take me off the streets.

Here is the story of how I fled Cuba and came to the United States.

After finishing college, I started taking freelance projects.

That was illegal. The Cuban government didn't allow people to make money working for foreign companies.

If you were lucky, you could get 2 years in jail. They called it "illicit enrichment."
We were a small group of friends. We met at my house every morning.

We paid a foreign national for Internet access. Cubans weren't allowed to buy it, so we had to get creative.

It was a 56kbs connection shared across 4 computers.
Read 13 tweets
28 Apr
Free machine learning education.

Many top universities are making their Machine Learning and Deep Learning programs publicly available. All of this information is now online and free for everyone!

Here are 6 of these programs. Pick one and get started!

Introduction to Deep Learning
MIT Course 6.S191
Alexander Amini and Ava Soleimany

Introductory course on deep learning methods and practical experience using TensorFlow. Covers applications to computer vision, natural language processing, and more.

introtodeeplearning.com
Deep Learning
NYU DS-GA 1008
Yann LeCun and Alfredo Canziani

This course covers the latest techniques in deep learning and representation learning with applications to computer vision, natural language understanding, and speech recognition.

atcold.github.io/pytorch-Deep-L…
Read 8 tweets
27 Apr
$5 only for the next 50 orders.

1,131 people have bought it. 99% 5-star ratings.

Don't like it, and you pay nothing.

Link here → gum.co/kBjbC/five
If you bought it already or aren't interested, like/retweet the original tweet, and you'll be supporting my work as much as if you were paying.

Thank you from the bottom of my heart!
40 left.
Read 5 tweets
27 Apr
Data is the core of machine learning.

It should not surprise you that most of the work you'll have to do is related to capturing, managing, processing, and validating data.

A few recommendations for those who would like to start.

1/7
As you get your feet wet, these are roughly some of the areas that you should cover:

• Data collection
• Data visualization
• Imputation
• Handling outliers
• Encoding
• Normalization and scaling
• Binning and grouping

2/7
Here is a good, introductory, free course provided by Google:

"Data Preparation and Feature Engineering in ML." — developers.google.com/machine-learni…

It covers the process of collecting, transforming, splitting, and creating datasets that machine learning algorithms can use.

↓ 3/7
Read 7 tweets
26 Apr
20 quotes that I use as inspiration to change my life.

Print them out. Keep them close. Read them frequently. Reflect on them and the wisdom behind every word.

Let's start:

Humans are allergic to change. They love to say, "We've always done it this way." I try to fight that. That's why I have a clock on my wall that runs counterclockwise.

— Grace Hopper
With engineering, I view this year's failure as next year's opportunity to try it again.

Failures are not something to be avoided. You want to have them happen as quickly as you can so you can make progress rapidly.

— Gordon Moore
Read 21 tweets
24 Apr
A book that will significantly help with your Python 🐍 skills:

• "Effective Python. 90 specific ways to write better Python." from Brett Slatkin @haxor.

amzn.to/3tM655V

Make sure you buy the second edition.

↓ 1/3 Image
The book contains 90 short lessons. Attached is the entire list.

Each lesson will take you a few minutes, which is extremely powerful:

• Finish lunch 🍱
• Grab the book
• Read one lesson
• Find a place in your code to apply it
• Put back the book on the shelf

↓ 2/3 ImageImageImageImage
Do this consistently, and you will significantly improve your Python skills.

Post a summary here on Twitter of what you learned for even better results.

This book works best for those who already write Python. It's not what you need to start from scratch.

3/3
Read 4 tweets

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