Are you afraid of the code interviews?😱😱😱
You're not alone!πŸ«‚

I've done many on both sides (candidate and interviewer)!

Here are some tips that helped me succeed:
πŸ‘πŸΎπŸ‘πŸΎπŸ‘πŸΎ

[1.5 minutes]

1/10🧡
During the interview you are being evaluated in many aspects and not only your coding skills

So while solving the technical questions, talk to the interviewer and explain what you are trying to achieve.

Communication is an important skill!

2/10🧡
Some people get anxious during the interview and might get blocked or forget even the basics. This is a very common problem

To overcome this what I did was:
β€’ Practice
β€’ Practice
β€’ Practice!

I solved many many problems on the white board before going for an interview

3/10🧡
Still on practicing, ask a friend to do a mock interview with you.

This is a great opportunity to understand how you feel when being interviewed and you can start to overcome your fear

Do these a couple of times until you feel confident!

4/10🧡
Study:
β€’ Data structures
β€’ Data structures
β€’ Common algorithms (sort, search, recursion)
β€’ Specifics or your area: Web, Mobile, ML, …

Nice to have:
β€’ Analysis of Algorithms (big O notation)
β€’ Graph theory

5/10🧡
The interviewer is not there to trick you. They are there to help you.

Ask questions!

If you didn't understand the problem, ask for clarification!

Ask about the input, problem assumptions, discuss corner cases

6/10🧡
Before starting to code, if possible, create your own set of input data. Add corner cases and problematic situations

Think about divisions by zero, out of bounds inputs, negative numbers, huge inputs

Don't start coding without a good understanding of the problem

7/10🧡
Please, know a little bit about the company you're applying to!!

You don't need to be a heavy user but at least know what their popular products do!

Bonus: If you could improve one of their products, what would it be?

8/10🧡
When I applied for the first time for Google, I had 14 years of experience but I didn't prepare enough

I failed and felt horrible for some months! This led to big changes (for the better) in my life and if you all want I can come back to this

9/10🧡
Summary:
β€’ Practice
β€’ Study the basics
β€’ Practice
β€’ Communicate
β€’ Mock interview

Do you want more tips on coding interviews?
Leave your questions in the comments!

Follow @gusthema so you don't miss out on this content

10/10🧡

β€’ β€’ β€’

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

Keep Current with Luiz GUStavo πŸ’‰πŸ’‰πŸŽ‰

Luiz GUStavo πŸ’‰πŸ’‰πŸŽ‰ 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 @gusthema

19 Oct
When I was studying for my technical interviews I used a couple of different resources

Here is a list of the 4 most important ones..

[And some bonus ones! 🎁🎁]

[1 minute of investment]

1/8🧡
1⃣ The Algorithm Design Manual by Steven S. Skiena

Is a great book to study basic and advanced algorithms! The text is very clear and good to learn or review.

2/8🧡
2⃣ Introduction to Algorithms by Thomas H. Cormen, Charles E. Leiserson, Ronald L Rivest, Clifford Stein

It's also known as CLRS

This is one of the main books on Computer Algorithms.
It's very deep!



3/8🧡
Read 8 tweets
6 Oct
A common question I get from developers is:

Which programming language do I need to know to start with Machine Learning?
πŸ‘…πŸ€–πŸ§ 

[1 quick⚑️ min]

1/5🧡
The easy answer is: If you know how to code well, that's all you need to start learning ML!

TensorFlow for example enables you to use ML in many languages like C++, Java, Kotlin, Swift, Objective C, JavaScript, Go, Julia, Scala, Ruby, C# and many others

Butβ€¦πŸ‘€

2/5🧡
The more realistic answer: Python🐍

Most of the ML samples, tutorials and content in general you'll see is written in Python

Understanding the basics of the language will definitely make your life MUCH easier

Here is a good place to start: docs.python.org/3/tutorial/

3/5🧡
Read 5 tweets
5 Oct
Do you want to start working with Machine Learning?

Let me give you 3 tips that I used to start my journey and that helped me a lot!

[2 min]

1/7🧡
1 - Start by understanding the basic concepts

This Machine Learning Crash Course cover all the basics and terms you'll need to start

Separate a couple of hours and have fun!

developers.google.com/machine-learni…

2/7🧡
This course has been updated many times to keep it fresh and to add more than the basic with:
β€’ Problem Framing
β€’ Data Prep
β€’ Clustering
β€’ Recommendation
β€’ Test and Debug
β€’ GAN

3/7🧡
Read 7 tweets
20 Sep
If you use the internet, there's a big chance that you already experienced the results of a Machine Learning Recommendation System

They, given a list of possibilities and your past choices, suggest items of the list that might interest you

Lets understand more about them

1/6🧡
Recommender Systems have a huge Impact:

β€’ 40% of app install on Google Play πŸ€–β˜ŽοΈ
β€’ 60% of watch time on YouTube 🐢🐱
β€’ 35% on purchases on Amazon πŸ’Έ
β€’ 75% of movie watches on Netflix 🍿

2/6🧡
Recommender Systems are very hard to train/evaluate/deploy:

β€’ Lots of features! 😰😱
β€’ Optimize to multiple objectives ↔️
β€’ Metrics can be misleading πŸ€”
β€’ Require lots of resources to be served πŸ’°πŸ’Έ

3/6🧡
Read 6 tweets
24 Jun
One term that I learned when I started studying ML is Hyperparameter.

What is it?
When should I worry about it?

Let me try to clarify it...

[3 min]

1/9🧡
First, what are the parameters of a ML model?

Those are typically the weights that you end up with after training your model. Example:

If you are creating a model to solve
AX + B = Y

A and B are the parameters you'll find. They are also know as the weights of the model

2/9🧡
Hyperparameters are the values that control the learning process.
Let's suppose we have the code in the image.

Hyperparameters could be: unit (from the Dense layer), learning_rate from the optimizer or even the batch_size

3/9🧡
Read 9 tweets
18 Jun
This week I've been posting about the itertools Python🐍 module.

If you want to improve your coding skills, one way is adding new tools to your toolbox

Itertools enables you to solve problems that would otherwise be absurdly hard to solve.

[2min]

1/7🧡
After you've learned the basic of Python, I'd suggest you go deeper in the collections manipulation:

β€’ Slicing
β€’ Comprehension
β€’ Generators
β€’ Iterators
β€’ Itertools
β€’ map/filter/zip

I've posted about all this content in the past, I can revisit if you'd like

2/7🧡
This week I've explained all functions on the itertools module

Starting by the basic ones:

3/7🧡
Read 7 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!

:(