BC MACHINE LEARNING

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Santiago
@svpino 4 years, 3 months ago 952 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

A surprising situation.

A machine learning model predicting 3 classes ends up with these results:

• Class A: 90% accuracy
• Class B: 80% accuracy
• Class C: 70% accuracy

Class C seems to be the worst-performing.

But you know already that I'll say it isn't. ↓

Here is the correct answer: We don't know yet which class is the worst.

This is important to understand, so keep reading.

Many people make this same mistake every day and try to fix things that ain't broken.

We are missing something, so let's go and get it.

How about if we ask a friend to look at the dataset manually?

Let's say these are the results of our friend doing the job:

• Class A: 95% accuracy
• Class B: 100% accuracy
• Class C: 71% accuracy

Do you see what just happened?

The model is actually really accurate when predicting Class C! 70% versus 71% when done by a human.

Class B, however, is a disaster: 80% versus 100% when done manually.

Class B seems to be the worse performing class!

The work that our friend did is called a "baseline."

Without having it, it's hard to determine how good are the results of a model.

I've seen tons of money down a drain just because teams didn't create a baseline beforehand.

But now, that won't happen to you 😉.

Santiago
@svpino

I'll blow your mind with a technique you aren't using yet.

Sometimes, you want your system to do exactly the opposite of what your machine learning model thinks you should do.

Let me convince you. ↓

I'm going to start with a nice problem:

Imagine a model that looks at a picture of an electrical transformer and predicts whether it's about to break or not.

Don't worry about how the model does this. We are going to focus on the results instead.

There are 4 possible results for this model:

1. It predicts a bad unit as bad.
2. It predicts a bad unit as good.
3. It predicts a good unit as bad.
4. It predicts a good unit as good.

#2 and #3 are the mistakes the model makes.

Assuming we run 100 units through the model, we can organize the results in a matrix:

• The rows represent the "actual" condition of the transformer.

• The columns represent the "prediction" of the model.

We call this a "Confusion Matrix."

This is how we can read this confusion matrix:

• 60 bad units were predicted as bad.
• 3 bad units were predicted as good.
• 7 good units were predicted as bad.
• 30 good units were predicted as good.

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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.

Santiago
@svpino

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.

Santiago
@svpino

Here is a simple example of a machine learning model.

I put it together a long time ago, and it was very helpful! I sliced it apart a thousand times until things started to make sense.

It's TensorFlow and Keras.

If you are starting out, this may be a good puzzle to solve.

The goal of this model is to learn to multiply one-digit

It is a good example of coding, what is the model?
— Freddy Rojas Cama (@freddyrojascama) February 1, 2021

More from Machine learning

emmi
@emmibevensee

The "polarization is the problem" narrative to me is bad because it implies the status quo was a stable and acceptable set of trade-offs. It's the equivalent of a pollyanna "why can't we all get along" but the we in question is white supremacy and its targets.

like i understand that conflict mediation requires mutual concessions (i did my MA in conflict studies) and while it's important to meet people's deep needs across spectrums of difference, certain things are just not up for negotiation.

Also while peacebuilding work is good. It's not just "seeing each other as human" it's literally about transforming structural issues. (hence Galtung's distinction between positive and negative peace wherin negative peace is like a ceasefire and positive is a transformed society.

And I think that to whatever extent that kind of peacebuilding work is applicable, it's not between fascists and people who think fascists are bad. Fascists are not invited. They are only invited if they seize territories and can't be crushed. Then secret negotiations.

The US is always like "we don't negotiate with terrorists" but literally every president negotiates with who they consider to be terrorists. It's all just down low. But that's just because counter-insurgency failed.

IM POCUS Focus
@IMPOCUSFocus

A tweetorial on optimal machine settings for B line image acquisition, with a focus on: focal position at pleura, harmonics off, and increased far gain.

Inspired/based on the recent article - https://t.co/vv2xBSZm6N
@cameron_baston @IsaacMatthiasM1

#POCUS #IMPOCUS

1/18

Let's start with some polls
We will stick to low frequency probes here (i.e. curvilinear and phased array - linear has its own purpose for detailed pleural assessment)

Which preset do you prefer for B line assessment?

2/

What depth do you typically set?

3/

After selecting preset and selecting depth, do you ever adjust any other machine settings to optimize B line assessment?

4/

Importantly, there is no right answer to the above questions!

We won't discuss much about preset or probe type. But we will discuss machine settings to optimize B line quality, based on
1) Theory based on physical basis of B lines
2) In vitro study
3) Study in patients

5/

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Alejandro Piad Morffis
@AlejandroPiad

This is a Twitter series on #FoundationsOfML.

❓ Today, I want to start discussing the different types of Machine Learning flavors we can find.

This is a very high-level overview. In later threads, we'll dive deeper into each paradigm... 👇🧵

Last time we talked about how Machine Learning works.

Basically, it's about having some source of experience E for solving a given task T, that allows us to find a program P which is (hopefully) optimal w.r.t. some metric

I'm starting a Twitter series on #FoundationsOfML. Today, I want to answer this simple question.

\u2753 What is Machine Learning?

This is my preferred way of explaining it... \U0001f447\U0001f9f5
— Alejandro Piad Morffis (@AlejandroPiad) January 12, 2021

According to the nature of that experience, we can define different formulations, or flavors, of the learning process.

A useful distinction is whether we have an explicit goal or desired output, which gives rise to the definitions of 1️⃣ Supervised and 2️⃣ Unsupervised Learning 👇

1️⃣ Supervised Learning

In this formulation, the experience E is a collection of input/output pairs, and the task T is defined as a function that produces the right output for any given input.

👉 The underlying assumption is that there is some correlation (or, in general, a computable relation) between the structure of an input and its corresponding output and that it is possible to infer that function or mapping from a sufficiently large number of examples.

$Pratham Prasoon \U0001f680$

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)

Anson Horton
@AnsonHorton

1/ @werat asked about whether the debugger was using the C# compiler or language service in VS 2002. It was not. The debugger has a component called an ‘expression evaluator’ that is provided per language and is responsible for parsing and evaluating expressions when stopped at a

2/ breakpoint. For example, if you type into the immediate window, hover over a variable, type into the watch window, etc. the expression evaluator is involved. The debugger and the language service are actually deeply integrated in a number of scenarios in VS, which may

3/ initially seem surprising. I may talk about more of these scenarios in the future, but to give a flavor, when you set a breakpoint at design time the language service is involved, when you are using Edit and Continue the LS is involved, the range of what is being evaluated

4/ when you get a debugger data tip, completion lists when typing in the data windows or immediate window, etc. Prior to VS 2002, there were distinct debug environments tailored to each target customer (VB/VBA, C++, VJ, VBScript, TSQL, FoxPro, Fortran, etc.). The goals of the

5/ VS 2002 debugger included unifying the debugger backend components and providing a single UI stack that would enable new scenarios (for example, a callstack across languages). Expression evaluators are the architecture that separate the language specific pieces from the

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SK
@sk_diary1

Kolaru Pathigam-Thevaram hymn composed by ThiruGnana Sambandar- #Thread

In Tamil Kol means planets,Aru means cut- set of songs in Kolaru Pathigam addresses all Navagrahas& last 2 lines of every song with end a plea to Bhagwan Shiva to reduce/erase the ill effects of Navagrahas

கோளறு பதிகம் - This pathigam was sung by Thirugnana Sambandar at Thirumaraikadu Kshetram -Vedaranyam,Tamilnadu

Thirugnana Sambandar & Appar(Thirunavukkarasar) travelled together to various Shiva Alayam to spread shivam & bhakti among people.They both reached Thirumaraikadu.

Thirumaraikadu(Vedaranyam) -
Appar & Sambandar were asked to enter the temple through side entrance.The main door was locked by Vedas many years ago.Appar&Sambandar sang devotional hymns praising Shiva, after which the gates opened & closed.After which main door opened for all.

After darshan of Bhagwan Shiva at Thirumaraikkadu,Sambandar received a message to travel to Madurai.
During that time, Samanam was on the rise in the Pandya Kingdom.The Pandya King converted to Samanam.The Queen Mangaiyarkkarasi was a staunch Shiva devotee and was upset.

Kularchirai Nayanar ,Chief Minister of Pandya kingdom was in agony by the turn of events.Queen requested Kulachirai Nayanar to escort Thiru gnana Sambandar to Madurai.Kularchirai Nayanar met Thiru gnana Sambandar at Thirumaraikkadu & requested him to visit Madurai.

Jaya_Upadhyaya
@Jayalko1

SRI KANTESH HANUMANTHA, KADARAMANDALAGI (KAR)
#bharatmandir

KANTESHA means Prabhu full of brightness.
Here, Sri Hanuman appears with a front face and sparkling eyes. Earlier, the village was also called KANTESHPURI on the name of Kantesha Hanuman.

Several thousands of years ago, Hanuman lived in this village. He once saw the Sun and mistaking it to be a fruit, began flying towards it. Since then, this village came to be known as Kadara Man Dalagi. (Kadar means rays, mandala is cluster of rays).

It is believed that King Janmejaya had set up the shrine to get rid of his difficulties.
There is a small pond on the right side of the kshetram where Teppotsava (Float festival) is celebrated.

Kanaka Dasa has praised Sri Kantesha in his various poetic compositions.

Kanaka Dasa was the first devotee to popularize the power of Kantesha. It is said that once Kanaka Dasa was deeply wounded in a battle. To seek blessings, he visited Tirupati but Sri Venkatesha appeared in his dream and advised him to see Kantesha first before seeing him.

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@MaMaMia73189983

Following @BAUDEGS I have experienced hateful and propagandist tweets time after time. I have been shocked that an academic community would be so reckless with their publications. So I did some research.
The question is:
Is this an official account for Bahcesehir Uni (Bau)?

Bahcesehir Uni, BAU has an official website https://t.co/ztzX6uj34V which links to their social media, leading to their Twitter account @Bahcesehir

BAU’s official Twitter account

BAU has many departments, which all have separate accounts. Nowhere among them did I find @BAUDEGS
@BAUOrganization @ApplyBAU @adayBAU @BAUAlumniCenter @bahcesehirfbe @baufens @CyprusBau @bauiisbf @bauglobal @bahcesehirebe @BAUintBatumi @BAUiletisim @BAUSaglik @bauebf @TIPBAU

Nowhere among them was @BAUDEGS to find

Mo Rajabifard
@morajabi

👨‍💻 Last resume I sent to a startup one year ago, sharing with you to get ideas:

- Forget what you don't have, make your strength bold
- Pick one work experience and explain what you did in detail w/ bullet points
- Write it towards the role you apply
- Give social proof

/thread

"But I got no work experience..."

Make a open source lib, make a small side project for yourself, do freelance work, ask friends to work with them, no friends? Find friends on Github, and Twitter.

Bonus points:

- Show you care about the company: I used the company's brand font and gradient for in the resume for my name and "Thank You" note.
- Don't list 15 things and libraries you worked with, pick the most related ones to the role you're applying.
-🙅‍♂️"copy cover letter"

"I got no firends, no work"

One practical way is to reach out to conferences and offer to make their website for free. But make sure to do it good. You'll get:

- a project for portfolio
- new friends
- work experience
- learnt new stuff
- new thing for Twitter bio

If you don't even have the skills yet, why not try your chance for @LambdaSchool? No? @freeCodeCamp. Still not? Pick something from here and learn https://t.co/7NPS1zbLTi
You'll feel very overwhelmed, no escape, just acknowledge it and keep pushing.

Erik Torenberg
@eriktorenberg

1/“What would need to be true for you to….X”

Why is this the most powerful question you can ask when attempting to reach an agreement with another human being or organization?

A thread, co-written by @deanmbrody:

Next level tactic when closing a sale, candidate, or investment:

Ask: \u201cWhat needs to be true for you to be all in?\u201d

You'll usually get an explicit answer that you might not get otherwise. It also holds them accountable once the thing they need becomes true.
— Erik Torenberg (@eriktorenberg) February 27, 2018

2/ First, “X” could be lots of things. Examples: What would need to be true for you to

- “Feel it's in our best interest for me to be CMO"
- “Feel that we’re in a good place as a company”
- “Feel that we’re on the same page”
- “Feel that we both got what we wanted from this deal

3/ Normally, we aren’t that direct. Example from startup/VC land:

Founders leave VC meetings thinking that every VC will invest, but they rarely do.

Worse over, the founders don’t know what they need to do in order to be fundable.

4/ So why should you ask the magic Q?

To get clarity.

You want to know where you stand, and what it takes to get what you want in a way that also gets them what they want.

It also holds them (mentally) accountable once the thing they need becomes true.

5/ Staying in the context of soliciting investors, the question is “what would need to be true for you to want to invest (or partner with us on this journey, etc)?”

Multiple responses to this question are likely to deliver a positive result.