BC MACHINE LEARNING

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Santiago
@svpino 3 years, 4 months ago 707 views

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For a long time, I didn't understand how to use Virtual Environments in Python 🐍.

If this is just, let's end it here and now: 🧵👇

[2] Virtual Environments let you deal with the dependencies that your code has with external Python libraries.

It avoids having conflicts when your projects depend on different versions of the same library.

👇

[3] Let's imagine that you are building your first Python project and you install the "requests" library:

pip install requests

You get version 2.24.0 installed in your system.

👇

[4] A month later, you decide to work on your second project. It also needs the "requests" library.

But the latest version is not 2.24.0 anymore.

Now version 3 is available, and that's the one you want to use!

👇

[5] You could upgrade your entire system to version 3, but then you'll be potentially breaking the first project you built that depends on 2.24.0!

Can you imagine this happening on a server with many more applications running?

👇

[6] Virtual environments solve this problem.

The first step for every new project is to create a virtual environment for it.

Some people have a central location where they store all environments. I prefer to keep them inside the project folder.

👇

[7] You can create a new virtual environment with Python 3 using the following command:

python3 -m venv .myvenv

Then, you can use "source" to activate the environment.

At this point, you'll have full isolation for your project.

👇

[8] If you install any libraries within a virtual environment, they will never mess with the libraries installed at the system level or other virtual environments.

And this is great!

Here is a @realpython's article covering virtual environments: https://t.co/lgXqJDUlKw

[9] The built-in "venv" module is not the only way to create virtual environments. Here are other options:

- conda
- pipenv
- virtualenv

What's your choice?

More from Santiago

Santiago
@svpino

You gotta think about this one carefully!

Imagine you go to the doctor and get tested for a rare disease (only 1 in 10,000 people get it.)

The test is 99% effective in detecting both sick and healthy people.

Your test comes back positive.

Are you really sick? Explain below 👇

The most complete answer from every reply so far is from Dr. Lena. Thanks for taking the time and going through

Really doesn\u2019t fit well in a tweet. pic.twitter.com/xN0pAyniFS
— Dr. Lena Sugar \U0001f3f3\ufe0f\u200d\U0001f308\U0001f1ea\U0001f1fa\U0001f1ef\U0001f1f5 (@_jvs) February 18, 2021

You can get the answer using Bayes' theorem, but let's try to come up with it in a different —maybe more intuitive— way.

👇

Here is what we know:

- Out of 10,000 people, 1 is sick
- Out of 100 sick people, 99 test positive
- Out of 100 healthy people, 99 test negative

Assuming 1 million people take the test (including you):

- 100 of them are sick
- 999,900 of them are healthy

👇

Let's now test both groups, starting with the 100 people sick:

▫️ 99 of them will be diagnosed (correctly) as sick (99%)

▫️ 1 of them is going to be diagnosed (incorrectly) as healthy (1%)

👇

Santiago
@svpino

My recommendation to start learning how to deal with structured data: Kaggle's Pandas Tutorial.

• Creating, Reading, Writing
• Indexing, Selecting, Assigning
• Summary Functions, Maps
• Grouping, Sorting
• Data Types, Missing Values
• Renaming, Combining

100% Python 🐍.

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Santiago
@svpino

Some of the things I've learned in more than 20 years in the tech industry.

You need to hear these.

🧵👇

Listen to more people who don't look like you, don't speak your language, and don't come from the same place you do.

We aren't doing this near enough.

Small habits compound.

No small improvement is too small.

Just aim for something new every day, and you'll be surprised at the end.

Take responsibility.

It doesn't really matter how you feel, I'm sure you could have done better.

Always keep the big picture in mind and never lose the forest for the trees.

Be the person that pulls everyone out of the rabbit holes.

Santiago
@svpino

Beginners guide to start with machine learning.

What you need:

1. A programming language
2. A place to write and run code
3. A way to deal with data
4. A way to visualize results
5. A cool algorithm
6. An introductory course
7. A project to solve

Here are my recommendations.

Most people recommend Python to start.

I do too.

You can do machine learning with many different languages, but today, Python is the best option.

My advice: Get comfortable writing code before looking into machine learning.

You don't have to be a great developer to start.

But if you are, it helps.

Everything you know about building software is helpful to build machine learning systems.

Good developers have the odds in their favor.

"How much Python do I need to know before starting?"

If you ask, you aren't ready yet.

Ideal scenario: You should be comfortable building software. Most people get here within a year.

Let's move on to the 2nd item from the list: A place to write and run your code.

Get familiar with Google Colab.

• It's free.
• Requires no setup to start.
• It's available from anywhere.

Alternative: Kaggle.

Santiago
@svpino

I learned enough AI/ML in 12 months to change my life forever.

You can do the same, and it all starts with a killer process to learn new things.

You can steal my approach. Every detail on the latest issue of my newsletter: https://t.co/9gaenLByFb.

Make it work for you.

More from Machine learning

Ram Bhupatiraju
@RamBhupatiraju

Happy 2⃣0⃣2⃣1⃣ to all.🎇

For any Learning machines out there, here are a list of my fav online investing resources. Feel free to add yours.

Let's dive in.
⬇️⬇️⬇️

Investing Services

✔️ @themotleyfool - @TMFStockAdvisor & @TMFRuleBreakers services

✔️ @7investing

✔️ @investing_city
https://t.co/9aUK1Tclw4

✔️ @MorningstarInc Premium

✔️ @SeekingAlpha Marketplaces (Check your area of interest, Free trials, Quality, track record...)

General Finance/Investing

✔️ @morganhousel
https://t.co/f1joTRaG55

✔️ @dollarsanddata
https://t.co/Mj1owkzRc8

✔️ @awealthofcs
https://t.co/y81KHfh8cn

✔️ @iancassel
https://t.co/KEMTBHa8Qk

✔️ @InvestorAmnesia
https://t.co/zFL3H2dk6s

✔️

Tech focused

✔️ @stratechery
https://t.co/VsNwRStY9C

✔️ @bgurley
https://t.co/NKXGtaB6HQ

✔️ @CBinsights
https://t.co/H77hNp2X5R

✔️ @benedictevans
https://t.co/nyOlasCY1o

✔️

Tech Deep dives

✔️ @StackInvesting
https://t.co/WQ1yBYzT2m

✔️ @hhhypergrowth
https://t.co/kcLKITRLz1

✔️ @Beth_Kindig
https://t.co/CjhLRdP7Rh

✔️ @SeifelCapital
https://t.co/CXXG5PY0xX

✔️ @borrowed_ideas

Pratham Prasoon
@PrasoonPratham

Can you get a job in data science and machine learning without a college degree?

🧵👇

Short Answer: Yes.

Long Answer, keep reading 👇

(Advice from industry experts who I talked to.)

Companies are looking for people who add value.
In order to add value, you'll need skills. Simple as that.

Get the skills to provide value and you'll get the job.

In the age of the internet where everything is pretty much free, why do college degrees matter?

A college degree makes it easier to get the skills to get a job in machine learning or data science.

College degrees also help you make many useful connections and provides many opportunities in the form of internships and whatnot.

College degrees have their own place

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$Pratham Prasoon \U0001f680$

Pratham Prasoon 🚀...
@PrasoonPratham

Here's how I got started with my first machine learning project and you can too.
Let's take a look.

(This thread will take from zero to being a hero in machine learning, trust me)

(1 / 22)
🧵👇

Getting started with your first machine learning project might actually much easier than it seems, if I can do it, certainly anyone can.

I did not use:
- Any Math
- An expensive computer
- Complex programming concepts

(2 / 22)

Here's what I did use:

- A free GPU on Google Colab
- Python
- TensorFlow
- Numpy
- Pandas
- Kaggle
- Scikit-Learn
- Google
- StackOverFlow

(3 / 22)

This project was actually a Kaggle challenge based on the MNIST dataset which is a collection images of 70,000 hand written digits.

You can find the dataset here👇
🔗//kaggle.com/c/digit-recognizer

(4 / 22)

Before we go over the code of this project, it is highly reccomended that you complete this free course on YouTube👇

Machine Learning foundations course
🔗//youtu.be/_Z9TRANg4c0

Code👇
🔗//colab.research.google.com/github/PrasoonPratham/Kaggle/blob/main/MNIST.ipynb

(5 / 22)

Pratham Prasoon
@PrasoonPratham

Do you want to learn the maths for machine learning but don't know where to start?

This thread is for you.
🧵👇

The guide that you will see below is based on resources that I came across, and some of my experiences over the past 2 years or so.

I use these resources and they will (hopefully) help you in understanding the theoretical aspects of machine learning very well.

Before diving into maths, I suggest first having solid programming skills in Python.

Read this thread for more

Are you planning to learn Python for machine learning this year?

Here's everything you need to get started.
\U0001f9f5\U0001f447
— Pratham Prasoon (@PrasoonPratham) February 13, 2021

These are topics of math you'll have to focus on for machine learning👇

- Trigonometry & Algebra

These are the main pre-requisites for other topics on this list.

(There are other pre-requites but these are the most common)

- Linear Algebra

To manipulate and represent data.

- Calculus

To train and optimize your machine learning model, this is very important.

Quant@Python
@BeingHorizontal

Thread for beginners; How to learn machine learning.

Let’s start with something really simple and useful not just for Machine Learning.

Start with a Python library called pandas. It’s a huge library but it's mostly fun for traders because it's kind of rewarding to learn each function and how it gonna affect the way you handle the financial data.

Then learn some basic stuff about Python library called NumPy. Pandas is built on NumPy. Numpy is huge, you just need to understand some basic NumPy functions like NumPy shapes and NumPy arrays

If you understand pandas then you will understand NumPy arrays and shapes easily. Side note: Numpy shapes gonna play an important part in the deep learning model called LSTM - mainly used for time-series analysis(such as financial data) and Natural Language Processing (NLP)

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Strange things are afoot at the Circle K. Let’s sort it out.

[THREAD]

1/ Two nights ago, Rupert Murdoch called on Mitch McConnell, after hours. Since then, two Fox News-related Twitter accounts have not tweeted.

2/ Trump fired Sessions on Wednesday, replacing him with human dildo/Putin collaborator Matt Whitaker. Sessions had asked to stay until Friday and was told to leave immediately. So there was clearly some urgency to install the dildo...er, puppet.

3/ The Democrats won the SHIT out of the Midterms. Come January, the House check on Trump will leave him so hobbled, he’ll be like the dude from Misery.

4/ Trump went to Paris, ostensibly for an Armistice Day centennial event. He skipped the event, and much of the dinner tonight, because of “weather,” which everyone seems to agree is a bullshit excuse.

$Elon Musk\u2019s Meme \U0001f171\ufe0fot$

Elon Musk’s Meme 🅱️ot...
@theMemesBot

why do I hear boss music

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$Stephen Fasenfeld \U0001f600$

Stephen Fasenfeld 😀...
@fasenfeld

1. “Who Are Ireland’s Members Of The World Economic Forum Implementing The Great Reset In 2021 ? 🧵1/28

🕵️🔎 Politicians, Musicians, Clergy, Bankers, Journalists, Human Rights, Artificial Intelligence, Sustainability, Corporations & Agriculture

2. In previous threads I have looked at 🇮🇪 key players in the Trilateral Commission as well as 🇮🇪 people who have attended the Bilderberger meetings. I also looked at the 🇮🇪 in the Young Global Leaders which is a site run by the WEF. You will see a lot of crossover between them.

3. The purpose of this thread is to compile all the Irish members into one thread for ease of access and reading rather than having to dive through the WEF site. This is by no means definitive and I will be adding more over time when they pop out of the woodwork.

4. Ireland’s WEF members are drawn from all walks of life but can be split into 2 separate areas. The WEF calls the first category “people” and the 2nd one “agenda contributors”. In total Ireland has a minimum of 61 members. Some of the names will be familiar and others will not

5. In this thread I’m just going to concentrate on the 21 people (there are probably a lot more). There are also 40 “agenda contributors” which I will cover in a separate thread. The agenda contributors are those who write articles or do research for the WEF site.

Emma Hilton
@FondOfBeetles

This is Kuinini ‘Nini’ Manumua, the woman who was ultimately displaced by inclusion of Laurel Hubbard.

She’s 21, and it would have been her first Olympics.

Sara Benincasa
@SaraJBenincasa

Spent a quaint half hour in a cafe listening to a guy yell at his dad after his dad said that the women Trump molested wanted it: "Dad, that's like saying the Jews who died in the Holocaust were asking for it!" ENJOY YOUR TERRIBLE FAMILIES THIS WEEK!

"Mom, has a man ever touched you without your consent?"
"Of course."
"Did you report it?"
"No."
"Dad, your WIFE has been through this!"

Dad was unmoved and told the guy to stop arguing with him.

At this point we learned the boy child has allergies.

I forgot to remark upon the presence of the very cute grandson, who was very small and gave not one shit about the yelling. I believe a sister or aunt was present and feeling very stressed. I wanted to hand her a Xanax or seven.

It was really hard to not jump in and say, "Sounds like you guys are going to have a fun meal tomorrow!" so they could unite in hatred against me, the outsider, and stop squabbling. Instead I exchanged glances with a nearby fellow lady patron, who also emotionally ate a cookie.

Anyway, I want to thank the random family for yelling about rape and the Holocaust in an Israeli cafe in the US of A today because it reminded me that while this country isn't the greatest, it is inevitably my stupid favorite and I am never, ever bored.