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

Here's everything you need to get started.
🧵👇

 In this thread, we'll look at all the concepts in Python you need to know for machine learning along with free resources to help you out.

All of this is based on my experience of successfully teaching 300+ students how to code using Python.

(2 / 19
You can use many languages for machine learning, why Python?

Because of 2 reasons:
- Comparatively easier to learn than other languages
- Has the biggest and most mature community

This makes Python a no-brainer to learn for machine learning as a beginner.

(3 / 19)
These are the absolute basics which you must know about:

- Basic terminal commands
- Basic arithmetic (+,-,/,*)
- Accepting user input
- For & While loops
- Exception handling
- If-Else statements
- Functions, modules & Imports

(4 / 19)
Then comes the more tougher concepts which you must know about:

- Object oriented programming in Python:Classes, Objects, Methods
- PIP (Pypi)
- List slicing
- String formatting
- Dictionaries & Tuples
- Managing environments
- Dunder methods like __init__

(5 / 19)
This are even more advanced concepts but you do not need then to start machine learning:

- Lambda functions
- Built in libraries like CSV, requests, Sqlite
- Map and Filter
- *args and **kwargs
- Async
- Decorators

(6 / 19)
From what I've observed, most beginners just find it really difficult just to get the Python environment setup and then using the terminal becomes an even bigger nightmare for them.

Let's tackle this issue.

(7 / 19)
You need to install:
- Anaconda for managing environments (different versions of Python)
- Python3
- Machine learning packages like Sckit learn and TensorFlow using pip when needed

(8 / 19)
Anaconda installation guide for 👇

MacOS: 🔗docs.​anaconda.​com/anaconda/install/mac-os/
Windows: 🔗docs.​anaconda.​com/anaconda/install/windows/
Linux: 🔗docs.​anaconda.​com/anaconda/install/linux/

(9 / 19)
MacOS and Linux have Python pre-installed, for windows you'll have to install it yourself and it is really easy to mess up the install.

Here's a guide with step by step instructions which will help you.
🔗bit.​ly/3rbDoyl

(10 / 19)
After you do all of that, you need a place to write your code which is called a "code editor".

Here are some popular ones

- VS Code: Feature-rich
- Sublime: Light and simple
- Jupyter: Useful for prototyping
- Pycharm: Full-blown IDE i.​e has loads of features.

(11 / 19)
If all of that seems complicated to you, I suggest you use Google colab, Kaggle notebooks or repl.​it
These are online editors which have everything set up for you.

Not to mention colab and kaggle notebooks give you a free GPU for your machine learning workloads.

(12 / 19)
Links for these editors

Collab : 🔗colab.​research.​google.​com
Kaggle Notebooks : 🔗kaggle.​com/notebooks/welcome
Repl : 🔗repl. it

(13 / 19)
The Basic & Intermediate Python course on freecodecamp go over pretty much all Python concepts you need for machine learning which I have mentioned above.

Basics: 🔗youtube.​com/watch?v=rfscVS0vtbw
Intermediate: 🔗youtube.​com/watch?v=HGOBQPFzWKo

(14 / 19)
Another thing which most beginners skip is knowing how to use the terminal properly and the know-how of navigating around folders.

Here's a brilliant website which gives you an overview of the windows command prompt, enough for you to get started.

🔗bit.​​ly/34tmnGd

(15 / 19)
The story is a bit different on Linux and Mac, their terminals are extremely powerful and packed to the brim with features, here's a tutorial which will help you get started with the basics 👇

​🔗youtube.​com/watch?v=oxuRxtrO2Ag

(16 / 19)
Keep in mind that you should learn how to use the linux terminal because at some point in your machine learning journey you will have to deal with linux.

It is not important to learn it at the start but I do recommend it.

(17 / 19)
This tutorial will help you in knowing how to work with folders, this is important!

Windows: 🔗youtube.​com/watch?v=HDmwiJxzIrw
Mac: 🔗youtube.​com/watch?v=3TAEC-1YUZw
Linux: 🔗youtube.​com/watch?v=HbgzrKJvDRw

(18 / 19)
That's the end of the thread!

Consider following me if you want to see more content like this, cheers.

(19 / 19)

More from Pratham Prasoon

Pratham Prasoon
Pratham Prasoon
@PrasoonPratham
A simple guide on how to train your first neural network in under 10 minutes to kick-start your machine learning journey.

(+ no setup required and free extra resources)
🧵👇

For this exercise, you'll need :
- A computer/phone
- An internet connection
- Very basic Python knowledge
- Willingness to learn

What you do not need:
- Complex math
- An expensive computer
- A PhD

Math will come later on in your machine learning journey :)

(2 / 15)

Here's our problem,we are given data in which we are given the number of flats in a house and its corresponding price. Like a house with one flat is worth 10000, and 20000 for a house with 2 flats.

(3 / 15)


We can clearly tell that the price of the house increases by 10000 per extra flat however our computer does not know this and we won't it tell it about this, it'll have to figure things out on its own.

(4 / 15)

Here's the code👇

(5 / 15)
MACHINE LEARNING
Pratham Prasoon
Pratham Prasoon
@PrasoonPratham
This is how I got three job offers as a 16-year-old high school student.

( and why I rejected them )
🧵👇

June 2020.

I receive a DM from a college student in California. The message read something like this "Hey Pratham, I am one of the co-founders of XYZ Inc, a robotics company, we are looking to add enthusiastic people to our team, would you be interested?"

(2 / 11)

It was the first time I had ever been offered a job, so I said Yes! (I did reject it later)

There were a couple of interview rounds I had to go through. None of them included technical questions, which was interesting.

(3 / 11)

After the first interview, I saw the list of the roles I could apply for. I realized how little I knew, terms like "Ui/UX, ROS(Robot operating system)", at that time, I was overwhelmed.

(4 / 11)

I knew that this wasn't a job for me. I decided that I would reject this job role even if I cleared the second round, which I ended up doing.

(5 / 11)
LIFE
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Pratham Prasoon
Pratham Prasoon
@PrasoonPratham
Machine learning terms you must know about as a beginner.

🧵👇

These terms won't mean anything unless you know what Machine learning is all about.

> Machine learning is the process of making a program which allows a computer to learn from data.

The data could be anything, images, audio or even text.

(2 / 11)

In machine learning we use something called a neural network, this is essentially an imitation of the human brain.

> Neural Networks are a digital imitation of the neurons you see in the human brain.

(3 / 11)


In these neural networks, data flows through them and each neuron (the circle) has a numerical value which will change.

> The value of a neuron gets changes to something which is close to what we want each time the data passes through the neural network.

(4 / 11)


Think of the neurons as dials on a lock, you have to tune every dial to open the lock.

It is almost impossible for a human to tune thousands of dials like these, but a computer certainly can.

(5 / 11)
MACHINE LEARNING
Pratham Prasoon
Pratham Prasoon
@PrasoonPratham
Machine Learning for the Web developer in 2021.

The beginner's guide.​

🧵👇

I started machine learning as a web developer, if I can do it then anyone can.

This carefully curated thread will give you key insights into my journey and how you can make this transition, seamlessly.

(2 / 14)

"Machine learning is not what you think it is"

One of the main reasons why people find it difficult to get started with machine learning is because of the lack of information, and rightfully so.

(3 / 14)

Machine learning as a concept has existed since the 1950s, but has only become popular in recent years because of the exponential rise of advancements in computer hardware.

(4 / 14)

In short, it because of the sudden rise of this technology ,which was previously unknown to the general public, that there is a lot of misinformation around it.

(5 / 14)
MACHINE LEARNING
Pratham Prasoon
Pratham Prasoon
@PrasoonPratham
These are the tools you will need for machine learning in Python.

🧵👇

Anaconda

When you work in python, you'll be working with several frameworks and many of them work only on specific versions of python.

(2 / 13)

Now imagine downloading a new version of python and then installing it for every framework you want to work with 😬.

Meet Anaconda which allows you to run several versions of python. It comes pre-installed with several data science and machine learning frameworks.

(3 / 13)

Pip-env is also a way of maintaining several versions of Python and comes pre installed with Python.
You can use pip env or Anaconda, whichever works for you.

(4 / 13)

Jupyter Notebooks

Jupyter notebooks is an IDE just like VS code or Sublime. The special thing about jupyter is that you can parts of code in mini code editors called cells. This is great for prototyping and testing code.

(5 / 13)
MACHINE LEARNING

More from Machine learning

Jan Giacomelli
Jan Giacomelli
@jangiacomelli
🤔 Python generators

What are they? How to use them?

#Python

🧵Let's find out 👇

1️⃣ Python generators are lazy iterators delivering the next value when their .next() is called.

They are created by using the yield keyword

next() can be called explicitly or implicitly inside for loop

They can be finite or infinite


2️⃣ yield - where a value is sent back to the caller, but the function doesn’t exit afterward as with the return statement

The state of function is remembered.

For example, the number is incremented and sent back from yield at the consecutive call next()


3️⃣ Generator stores only the current state of the function - it generates next element on next() call and forgets the previous one -> it saves memory

For example, we don't need to store 1mio elements in memory to do something with each element


4️⃣ When you call a generator function generator object is returned - it's not executed yet

It executes only when next() is called

For example, that's why Exception is raised only on the next() call
MACHINE LEARNING
Ram Bhupatiraju
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
MACHINE LEARNING , ALL
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Alejandro Piad Morffis
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


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.
MACHINE LEARNING
Santiago
Santiago
@svpino
10 machine learning YouTube videos.

On libraries, algorithms, and tools.

(If you want to start with machine learning, having a comprehensive set of hands-on tutorials you can always refer to is fundamental.)

🧵👇

1⃣ Notebooks are a fantastic way to code, experiment, and communicate your results.

Take a look at @CoreyMSchafer's fantastic 30-minute tutorial on Jupyter Notebooks.

https://t.co/HqE9yt8TkB


2⃣ The Pandas library is the gold-standard to manipulate structured data.

Check out @joejamesusa's "Pandas Tutorial. Intro to DataFrames."

https://t.co/aOLh0dcGF5


3⃣ Data visualization is key for anyone practicing machine learning.

Check out @blondiebytes's "Learn Matplotlib in 6 minutes" tutorial.

https://t.co/QxjsODI1HB


4⃣ Another trendy data visualization library is Seaborn.

@NewThinkTank put together "Seaborn Tutorial 2020," which I highly recommend.

https://t.co/eAU5NBucbm
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Fionna O'Leary, \U0001f56f\U0001f1ea\U0001f1fa
Fionna O'Leary, 🕯🇪🇺...
@fascinatorfun
Thanks for this incredibly helpful analysis @dgurdasani1

Two questions. 1/ Does this summarise the AZ published data :
The plan is to extend the time interval for all age groups despite it being largely untested on the over 55yrs, although the full data is not yet published


Do we have the actual numbers of over 55yr olds given a 2nd dose at c12 weeks and the accompanying efficacy data?

Not to mention the efficacy data of the full first dose over that same period?

I’d quite like to know whether I am to be a guinea pig & the ongoing risks to manage

You attached photos of excerpts from a paper. Could you attach the link?

Re Pfizer. As I understand it the most efficacious interval for dosing was investigated at the start of the trial.


Here’s the link to the

I’ve got to say that this way of making and announcing decisions is not inspiring confidence in me and I am very pro vaccination as a matter of principle, not least because my brother caught polio before vaccinations available.
MACHINE LEARNING

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Thiruvairanikulam Mahadeva Temple
Ernakulam Kerala🚩
#temples

Temple is known as Sabarimala of Women

Thiruvairanikulam Mahadeva Temple is situated on the banks of the Periyar River. Siva Temple has a separate sannidhi for Parvathi Devi which will be open only for 12 days a year


The Nadathurappu Mahothsavam happens every year on Malayalam month of Dhanu. On opening day, a grand procession starting from Akavoor Mana carries the ornaments of Devi to the temple. Swayamvara Archana is the main pooja here to clear the obstacle in marriages.
Legend is that 👇


Vigraham existed in another place called Iranikulam. A Namboodiri of Sreemoolanagaram used to visit the Iranikulam temple regularly. Akavoor Chathan, a boatman will take him to the Iranikulam temple and back. Because of Bhakthi of Namboodiri, Shiva traveled with him to his place.


Akavoor Chathan identified Siva chaitanyam and their family built a temple here. Parvati devi herself will cook Nevidyam here for Shiva, which was witnessed by a priest. Devi was angry at this and decided to leave the place. But when the priest offered his sincere apology👇


Devi blessed him and told that she will be present here 12 days in a year. Thus the period which begins from Thiruvathirai Day in Dhanu is known as the Nadathurappu festival.
Temple Nada opens today night.
Picture credit: Google.
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Anshul Pandey
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@Anshulspiritual
BRAHMA VAIVARTA PURAN: IMPORTANCE AND CHARACTERISTICS.

This Puran introduces us to way of Vedas. On the request of Narad Muni Bhagwan Saavarni had preached this Puran. It is a summary of Dharma, Arth, Moksha etc.


Listening to this Puran one gets automatically attached to Vishnu and Shiva and realize that there is no difference between them. Vyasji divided this book into four parts. It has eighteen thousand shlokas. This whole book is in the form of dialogue between Suutji and Maharishi's.

The first part Brahmkhand, consists of Shrishti description. Here Shri is known as Para Brahma and description of Gokul is also mentioned, It also narrates the argument between Brahma and Narad in which both were defeated, and then Narad went to Shiva to attain more gyan.

Shivji advised him to go to Bhagwan Saavarni for this. Narad goes to Saavarni ashram to seek Knowledge and is totally amazed by the sorroundings.

Next is Prakriti khand which consists of dialogue between Narad and Saavarni where they discuss the

Importance of Shri Krishna through various stories. Then there is the discussion of Prakriti and its various hues. Listening to this gets you wealth.
Next is Ganesh Khand which describes the Punyak vrat done by Parvati ji. After this it narrates the birth of Kartikeya and Ganesh.
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Mo Rajabifard
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.
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Most software founders, particularly in B2B, need to get radically better at sales. @Steli , who is the best person for explaining the scrappy stages in the beginning and then building out a team with scripts and processes, wrote a guide to:

For technical founders it is irrationally, obscenely hard to reverse years of programming (ba dum bum) that sales is a value-destroying activity. Sales is CLEARLY a value-creating activity, contingent on you have a value-creating product.

The world will not drop what they are doing to adopt your work. This is particularly true in B2B, where simply building a better mousetrap won't overcome the activation energy required to get people with additional non-mice problems to prioritize changing mousetraps today.

This is very non-obvious for founders because founders are not often people who *want* to be sold to. We often come from a background where trying out tools is a bit of a fun hobby. We like looking at all the options, making charts, and ripping out partially complete tests.

"This week I unsuccessfully trialed four software options for automating that thing that has been killing us. Our actual production process remains the same as last week. Don't worry; this was a great use of time." is not a thing you want to write in a progress report to manager.
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Nyck de Vries
Nyck de Vries
@nyckdevries
Lately there have been various rumours in the media about myself and Jumbo in relation to Williams. To clarify things, Jumbo is not and will not invest any money in my career. 1/2

Of course we’re collectively looking at career opportunities, however this is certainly not our philosophy and strategy. I hope to announce my future plans soon, be patient 😉 2/2
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