Santiago Profile picture
20 Jun, 4 tweets, 1 min read
My favorite technical book:

Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow.

If you are looking to buy your first machine learning book, start here: amzn.to/2KPuRAo

Image
Prerequisites to get the most out of this book:

• Python
• NumPy
• Pandas
• Matplotlib

You don't need to be a math expert to read it.
The book is not hard to read.

Most machine learning books over-emphasize math. They are scary, dense, and feel like a puzzle rather than a story.

This is not it.

You can actually go through this one without vomiting first! 🤮
Today, I mostly use the book as reference.

Whenever I want to refresh my understanding of a concept, or read a different take on a technique.

When I first bought it, I read most of it starting from the beginning.

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with Santiago

Santiago Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @svpino

21 Jun
What's machine learning?

Not a framework. Not a different language. Not the latest "cool" thing around the Internet.

Thread: Let me convince you that machine learning is the best thing since sliced bread 🍞.
Let's start with a simple exercise:

"Write a function that returns 0 if a supplied number is even or 1 if the number is odd."

If you are a developer, I'm sure you know how to write this function. It should be simple, right?
To avoid using a specific syntax, let's represent this function as follows:

y = f(X)

Where:
• X → The input number
• y → The result (0 if even, 1 otherwise)
• f → The function that does the work

We can now get to the interesting part.
Read 20 tweets
18 Jun
I just went through 200+ applications for a machine learning position.

I think I figured out what works and doesn't in a resume.

Here are a few tips.
The question I want to answer when I read a resume:

• Should I call this person?

Anything that doesn't help me with this decision is working against you.
The most common problem I found when reviewing applications:

Most resumes are 90% noise and 10% signal. People bury relevant details in an ocean of useless information.

Fix this, and you increase your chances significantly.
Read 20 tweets
17 Jun
Here is a simple trick that improves the results of your models.

Best part: You'll surprise your team. Guaranteed.

Thread: What is Test-Time Augmentation, and how you can start using it today.

Let's start with Data Augmentation:

It allows us to artificially increase the size of a dataset without having to collect more data.

Data augmentation is key to improve the performance of our models.
Data augmentation is very popular when working with images.

We can apply different transformations to each image to obtain new samples:

• Cropping
• Rotations
• Flipping
• Zoom

We can then train the model with the augmented dataset and get much better results.
Read 10 tweets
15 Jun
If you are planning to get started with Machine Learning:

My introductory course is on sale:

• 50 copies @ $5, starting right now.
• Free copies for those who can't afford this.

gum.co/kBjbC/five

If you want to support my content, like/retweet this. Everyone wins.
10 copies sold, 40 copies left @ $5.
20 copies sold, 30 copies left @ $5.
Read 11 tweets
15 Jun
Do you know what's holding you back?

The same boring projects than everyone else is working on. How do you break off the mold and make a difference?

Thread: 7 machine learning projects that will teach you the technical skills you need to succeed out there.
Today, companies are dumping insane amounts of money on people with the right skills.

But here we are, showing up with the same "MNIST Digit Recognition" and "Iris dataset" experience.

These are good to start, but you need to take your learning to another level.
The good news for you: Most people can't be bothered.

Most people will bookmark this thread and will never do anything with it.

Even if you do one of these 7 projects, you'll be doing more than 99% of everyone who reads this!

It has never been easier to stand out!
Read 19 tweets
14 Jun
How close are we to building a truly intelligent agent?

Most scientists think we are still decades away, but today, a group of scientists from @DeepMind claims they know how to get there.

Let's talk about what's going on.
What is "Artificial General Intelligence" (AGI)?

An agent capable of learning any intellectual task than a person can also learn.

Today, AI has been limited to systems that can learn particular tasks. A system that can learn anything you teach it, just like a human, is AGI.
Unfortunately, there's no way to build such a general, intelligent agent without formulating a custom solution for every individual task.

This sucks. This doesn't scale. This doesn't get us to AGI.

But maybe we aren't that far off...
Read 16 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Too expensive? Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal Become our Patreon

Thank you for your support!

Follow Us on Twitter!

:(