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Gus (πŸ€–πŸ§ +🐍+πŸ₯‘πŸ—£οΈ) Profile picture
@gusthema
Oct 24, 2021 β€’ 6 tweets β€’ 2 min read β€’ Read on X
This week I posted about the Code interview!!!πŸ˜±πŸ˜­πŸ€“

Here's a summary if you missed it

[30 sec]

1/🧡
To start, You'll need some tips on how to succeed!πŸ‘πŸΎπŸ‘πŸΎ



2/🧡
To follow the tips and succeed you'll need good resources to study and practice!πŸ“šπŸ‘“

I've got you covered:

3/🧡
One of the tips I gave was to do mock interviews with your friends and since I'm your friend I did one for you:
πŸ‘πŸΎ (is this a high five?πŸ€”)



4/🧡
The mock interview had lots of great answers and insights!

That's why I summarized them to make it easier for you to follow! πŸ—œοΈπŸ—œοΈ



5/🧡
Do you have questions about the Code Interview process?
Leave them in the comments, I'll answer as many as I can!

So you don't miss my content, don't forget to share this thread with your colleagues and also to follow me! (@gusthema ) πŸ‘πŸΎπŸ‘πŸΎπŸ‘πŸΎ

6/🧡

β€’ β€’ β€’

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

Keep Current with Gus (πŸ€–πŸ§ +🐍+πŸ₯‘πŸ—£οΈ)

Gus (πŸ€–πŸ§ +🐍+πŸ₯‘πŸ—£οΈ) Profile picture

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More from @gusthema

Gus (πŸ€–πŸ§ +🐍+πŸ₯‘πŸ—£οΈ) Profile picture
Mar 14, 2023
Ok, since today is Pi (Ο€) day, maybe it's a good day to learn about it a little bit!

Here are some fun facts about the number Pi
πŸ€“

πŸ‘‡
Pi is the ratio of a circle's circumference to its diameter.

It is an irrational number, meaning it cannot be expressed as the ratio of two integers.

And its digits NEVER repeat in a regular pattern.

πŸ‘‡
As of Today, 100 trillion digits of Pi were calculated!!

The "last" 10 digits are: 43095295560

If all the digits were written to a txt file, with regular ASCII encoding, that would be a 100 Terabytes file! 🀯

You can learn more about it here:
cloud.google.com/blog/products/…

πŸ‘‡
Read 13 tweets
Gus (πŸ€–πŸ§ +🐍+πŸ₯‘πŸ—£οΈ) Profile picture
Mar 13, 2023
Learning how to apply Machine Learning for the Audio domain can be tricky as there are aspects related to the data that might not be obvious and it's not as popular of a topic as Image or Text

Don't worry! I got you covered!

Here are some tutorials to get you started:

πŸ‘‡
The first one you should take a look at is the Recognizing Keywords tutorial:

tensorflow.org/tutorials/audi…

This tutorial goes over some of the basics and it's a great start

πŸ‘‡
Building a model from scratch with great results is hard
πŸ˜“

Stand on the shoulders of giants using a pre-trained model!

Here is a tutorial doing just that: tensorflow.org/tutorials/audi…

This model can be easily used on mobile devices and on the browser!

πŸ‘‡
Read 8 tweets
Gus (πŸ€–πŸ§ +🐍+πŸ₯‘πŸ—£οΈ) Profile picture
Mar 8, 2023
πŸ¦πŸ¦…πŸ¦†πŸ¦‰πŸ¦œ+ πŸ€–πŸ§  = πŸ’°

I've been working with ML for the Audio domain for a while

At first I couldn't understand much but as I kept reading I managed to figure out some things.

Let me share some of the basic theory with you:
πŸŽ™οΈπŸ§‘β€πŸ«

πŸ‘‡
Sound is a vibration that propagates as an acoustic wave.

It has some properties:
β€’ Frequency
β€’ Amplitude
β€’ Speed
β€’ Direction

For us, Frequency and Amplitude are the important features.

en.wikipedia.org/wiki/Sound#Sou…

πŸ‘‡
An important aspect is that Sounds are a mixture of their component Sinusoidal waves (follow a sine curve) of different frequencies.

From the equation below:
β€’ A is amplitude
β€’ f is frequency
β€’ t is time

πŸ‘‡

gist.github.com/gustheman/9101… ImageImageImage
Read 15 tweets
Gus (πŸ€–πŸ§ +🐍+πŸ₯‘πŸ—£οΈ) Profile picture
Sep 12, 2022
"How do I learn Python?"
πŸ€”

3 tips:

β€’ Do one basic tutorial πŸ€“
β€’ Practice, practice, practice πŸ’ͺ🏾
β€’ Start/Find a project to apply what you learned 🧐

"Ok Gus, how about some links?"

πŸ‘‡
I have three very good Python tutorials to get you started:

1⃣ Kaggle course: kaggle.com/learn/python

β€’ Kaggle Kernels allow you to try the code in the browser
β€’ Very good pace of content
β€’ Fun and challenging puzzles

πŸ‘‡
2⃣ THE Python tutorial: docs.python.org/3/tutorial/

This is the official one and I like it very much

It's very direct on how things work without fun exercises but some people prefer this approach

πŸ‘‡
Read 9 tweets
Gus (πŸ€–πŸ§ +🐍+πŸ₯‘πŸ—£οΈ) Profile picture
Aug 29, 2022
When we talk about Decision Trees in Machine Learning, one of the most popular and powerful algorithms is the Gradient Boosted Decision Trees

Do you know how it works?πŸ€”

Let me give you an easy explanation of how it worksβ€¦πŸ‘€

πŸ‘‡
Gradient Boosted Decision Trees (GBDT) is an ensemble method -> it's based on a set of other smaller models

The smaller models are just Simple Decision trees, similar to the Random Forest algorithm

πŸ‘‡
Random Forest and GBDT both use a set of basic Simple Decision Trees but are trained and work differently

The idea of the GBDT algo:

➑️to improve your model's prediction, you add new trees that make its error (distance from its prediction to the real label) smaller

πŸ€”πŸ˜΅β€πŸ’«

πŸ‘‡
Read 9 tweets
Gus (πŸ€–πŸ§ +🐍+πŸ₯‘πŸ—£οΈ) Profile picture
Jul 28, 2022
What are Python🐍 decoratorsπŸŽ€?

Decorator is an Object Oriented pattern that allows behavior to be added to individual objects

They can be more efficient than subclassing and in some cases it can make your code 1000 faster!πŸ‘€πŸ€―

πŸ‘‡
Python supports this pattern and you can apply decorators to functions like this:

@some_decorator
def my_function():
Some_code

This is also called metaprogramming.

πŸ‘‡
There are many built-in decorator available, like: lru_cache, data_class, singleton

lru_cache creates an automatic cache for you.
The cache, in the code below, has a ~1000 times improvement!
⚑️🀯
Read 5 tweets

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