Santiago Profile picture
3 Apr, 4 tweets, 1 min read
The Python 🐍 community on Twitter is amazing!

If you are a Python developer or you are looking to get started, introduce yourself below and let others connect with you👇
Hi 👋, I'm a machine learning engineer, and I've been coding exclusively with Python for 7 straight years.

I believe that Python is one of the most versatile languages you can learn today, and it's an investment with the potential to change your life.
The best part about this are the connections that this enables.

People saying hi, making study groups, asking questions, and helping each other.

Make sure to look through the comments. A lot of likeminded people willing to partner with you and do this together!
Almost 700 Python developers have introduced themselves! This community is really cool!

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More from @svpino

5 Apr
Many people who want to start with machine learning face a big hurdle:

They think they can't do it at their current company.

But more often than not, this is not the case. This is a thread about things you can do to get past this.

↓ 1/12
First, don't worry if your company doesn't have a machine learning engineer position yet.

Look at this as a good opportunity!

Nobody has any expectations about the job yet, so you'll get to set the pace.

↓ 2/12
Focus on doing the work. The actual position, title, compensation, and other details will follow later.

Here is where you need to get creative, and these are two different strategies that I've seen working.

↓ 3/12
Read 12 tweets
4 Apr
Learning a new language is not an obvious decision, especially when you are just starting in the industry.

Here are 10 frequently asked questions about learning Python 🐍. Hopefully, these give you the answers you are looking for.

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1. Can I learn Python for free?

Yes. There are multiple YouTube videos, tutorials, and courses that will teach you Python for free.

But if you can afford it, I'd recommend you find a good MOOC that gives you some structure.

↓ 1/10
2. Is Python hard to learn?

It's not, especially compared with other languages out there.

That being said, becoming an expert is a life-long journey.

But one year of experience is more than enough for you to do whatever you decide to do.

↓ 2/10
Read 13 tweets
3 Apr
25 True|False machine learning questions that are horrible for interviews but pretty fun to answer.

Most importantly: they will make you think and will keep your knowledge sharp.

These are mostly beginner-friendly.

↓
↑

1. A "categorical feature" is a feature that can only take a limited number of possible values.

2. Precision is a performance metric that defines a classification model's ability to identify only relevant samples.

↓
↑

3. Recall is a performance metric that defines a classification model's ability to identify all relevant samples.

4. One-hot encoding is an excellent solution to transform categorical features with high cardinality.

↓
Read 14 tweets
2 Apr
You want to build a function to retrieve a value from a sequential list of unordered elements.

What would be the best approach?
You can assume that the size of the list is unknown.

Oh, sorry if this was confusing.

By "sequential list" I meant that elements come one after the other in memory. Think of a regular array.

It doesn't mean that you can't access elements out of order.

Read 4 tweets
2 Apr
When we start with machine learning, we learn to split our datasets in testing and training by taking a percentage of the data.

Unfortunately, this practice could lead to overestimating the performance of your model.

↓ 1/7
Imagine a dataset of pictures with people doing signals with their hands.

As we were told, we take 70% of the images for training and the remaining 30% for testing. We are careful to maintain the original ratio between classes.

How could this be a problem?

↓ 2/7
There are a lot of pictures of Mary in the dataset. She is showing different signals with her hands.

Also Joe. He was a model too that participated in the creation of the dataset.

↓ 3/7
Read 10 tweets
1 Apr
Pick one of these two.

They will both help you write better Python.
Both of these are great books to open from time to time and read an individual section.

They give you bite-sized tips and advice that you can incorporate immediately into your work.

Replace 30 minutes of Netflix every week with some reading.

Read 4 tweets

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