Many machine learning courses that target developers want you to start with algebra, calculus, probabilities, ML theory, and only then—if you haven't quit already—you may see some code.

I want you to know there's another way.

↓

2. For me, there's no substitute to seeing things working, trying them out myself, hitting a wall, fixing them, seeing the results.

A hands-on approach engages me in a way pages of theory never will.

And I know many of you reading this are wired just like me.

3. I feel that driving a car is a good analogy.

While understanding some basics are necessary to start driving, you don't need to read the entire manual before jumping behind the wheel.

As long as you practice in empty parking lots and backroads, you'll be fine.

4. As you make your way to public roads, you can start incorporating more of the theory that will help you stay safe.

At this point, that theory won't be lost on you: your hours behind the wheel will help you make the necessary connections.

Things will start clicking quick.

5. I've talked to people struggling with derivatives that have no idea why or when they'll become helpful.

I've seen others memorizing what eigenvectors are, or manually transposing matrices because "that's what it takes."

Honestly, for the most part, it's not.

Learn Data Engineering in a free online course from @DataTalksClub!

- Batch processing
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More information

Developers,

If you are still learning programming, or already getting ready for interviews then you should learn Data Structures & Algorithms. They can be intimidating but if you take the time and practice every day they're not that bad. Below I'm sharing a really good resource:

This is a playlist on YouTube from MIT. It has all the videos of every class they had for the semester in 2020.

MIT is the best school for computer science so you know these professors are the best of the

This is the course itself, if has a link to the playlist I just shared above, but also links to the notes, books used in the class, tests, everything.

I really hope someone uses it because this can make anyone good at

What are NFTs?🔥

Learn 'everything' about them!

Le Thread🧵👇🏽

NFT is short for Non-Fungible Tokens

They may look like pictures, but there's a lot under the hood.

NFTs are:

- one-of-a-kind
- rare
- are non-fungible
- can be sold

Any digital item can be an NFT - audio, photo, video, etc

🏞 Artworks are the most popular kind of NFTs

Non-fungible 🔐

NFTs are termed non-fungible because they can't be traded for other NFTs

They're one-of-a-kind and each NFT holds a specific value.

An NFT can't be exchanged for another NFT cos NFTs have different values unlike money where 1$ is worth 1$, and 2$ worth 2$...

Under the hood 🕵🏾‍♂️

NFTs may look like images you can just 'copy-and-paste', but they have unique metadata attached to them which looks like this 👇🏽

The images we see are just a representation of this metadata. So technically, this is all an NFT is 👇🏽👇🏽

So why are NFTs 'Expensive'🤔💭

- they can be traded easily through NFT marketplaces

- they allow buyers to own the original item, acting as a collector's item

- they are rare, unique, and scarce since only one original version exists, thus, making them expensive

Are you looking for ways to start Data Science and Machine Learning? 🤔

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