BC MACHINE LEARNING

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Pratham Prasoon
@PrasoonPratham 4 years, 6 months ago 1160 views

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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

However that does not mean that you cannot get into these fields without a degree, it'll just take more work.

For machine learning and data science you mainly need 3 skills:

- The theoretical part which mainly includes math
- The practical part which includes programming skills
- An understanding of the industry in which one is applying machine learning and data science

Most people will probably stop here because of the math.

Math is important, but not when you are starting out. You can learn math as and when you need it, programming is actually the more important part.

Start by having strong fundamentals in programming.
This is more important than you think it is.
Python, R and Julia are some of the options out there.
Python is the most recommended for several reasons.

Next, work on a few Kaggle challenges by taking the help of submissions of other users, the docs and the internet.

While you are making these models, try to research a bit more about what's going on under the hood.

If you're making a neural network, try researching about the some of the activation functions you have used in the model.

This was just one approach to learning the skills needed for machine learning and data science. Do what works for you, just get the job done.

And of course, this isn't going to be a very easy process.

It could take more than a year before you could get ready for applying to jobs.

That doesn't mean it can't be done.

More from Pratham Prasoon

Pratham Prasoon
@PrasoonPratham

How to learn Python for machine learning. 🐍

The beginner's guide.
(based on my real life experience of mentoring 300+ students)

🧵👇

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

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)

$Pratham Prasoon \U0001f680$

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)

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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)

Pratham Prasoon
@PrasoonPratham

Are you planning to learning machine learning this year?

These are the Python frameworks you need to learn as an absolute beginner.

🧵👇

It can be overwhelming seeing all the machine learning frameworks at once and not even knowing what they do.

I made this thread so that your machine learning journey becomes just a little bit easier.

(2 / 11)

This thread will only focus on Python frameworks.

Why?
Because Python is the most common path into machine learning.

( If you have experience with any other language then learning Python will not be difficult at all. )

(3 / 11)

Here's the entire list:

- Pandas
- Numpy
- Matplotlib
- TensorFlow
- PyTorch
- Keras
- Scikit Learn

Let's see what they do.

(4 / 11)

You'll have to interact with csv files or databases on a regular basis to access data in machine learning, pandas helps you do just that.

The cool thing about Pandas is that it actually doesn't change the original data...

(5 / 11

Pratham
@PrasoonPratham

There are a million machine learning tutorials and courses out there which makes it really hard to choose the right one for you.

Here are some that I really like that you might find useful.
🧵 👇🏻

Before we begin, here's some unsolicited advice.

It is not about how many courses you take that matters but the problems that you solve with your knowledge.

You can take any combination of courses and tutorials from this list that you think will be useful.

Python crash course by Traversy Media (YouTube)

• Introduces you to a lot of basic concepts in Python
• Only 1.5 hours long

Intermediate Python course (YouTube)

• Helps you understand some of the more difficult concepts in Python

The neural networks series by 3blue1brown (YouTube)

• Visually explains neural networks
• Short and concise

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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)

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.

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Caio Rolla
@caio_rolla

Starting a new project using #Angular? Here is a list of all the stuff i use to launch my projects the fastest i can.

A THREAD 👇

Have you heard about Monorepo? I created one with all my Angular (and Nest) projects using https://t.co/aY5llDtXg8.

I can share A LOT of code with it. Ex: Everytime i start a new project, i just need to import an Auth lib, that i created, and all Auth related stuff is set up.

Everyone in the Angular community knows about https://t.co/kDnunQZnxE. It's not the most beautiful component library out there, but it's good and easy to work with.

There's a bunch of state management solutions for Angular, but https://t.co/RJwpn74Qev is by far my favorite.

There's a lot of boilerplate, but you can solve this with the built-in schematics and/or with your own schematics

Are you not using custom schematics yet? Take a look at this:

https://t.co/iLrIaHVafm
https://t.co/3382Tn2k7C

You can automate all the boilerplate with hundreds of files associates with creating a new feature.

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

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.

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Jaya_Upadhyaya
@Jayalko1

AHOBILAM NARASIMHA SWAMY KSHETRAM: KURNOOL (AP)
#andhratemples

Ahobilam is the place where Prabhu appears in his fierce form, called Ugra Narasimha, who is Svayambhu (self-manifest).
Ahobilam is one of the 108 Divya Desams. It has 9 shrines for different forms of Narsimha.

Ahobilam was the exact place where Sri Narasimha appeared and tore apart Hiranyakashipu to save Prahlad. At that moment, all the Devas appeared and praised him as Ahobala (Aho is mighty and bala is strength). So the place came to be called Ahobilam.

Out of the 9 shrines, most famous is the Ahobila Narasimha Swamy where Prabhu is seen as Ugra Narasimha.
In another shrine, Prabhu appears as Malola Narasimha Swamy. Malola means beloved of Lakshmi. Here Prabhu is in peaceful mudra with his consort Ma ChenchuLakshmi.

Jwala Narasimha Swamy shrine is the actual spot where the fierce anger of Prabhu reached its culmination when he tore Hiranyakasipu.

Ugra Stambham is the pillar from which Narasimha appeared with such force that the entire hill split into two.

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.

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Delilah S. Dawson
@DelilahSDawson

Hello, writers! How about a thread on LITERARY AGENTS? How to get one, how to talk to one, how to keep one happy. Spoiler alert: I am 100% pro agent and can't imagine not having one on my side. 1/

Why would you want a literary agent?
* you want to be traditionally published
* you want someone experienced to help guide your career
* you want to learn how to edit like a pro
* you want to sell foreign and movie rights
* you want answers to your newbie questions 2/

Why you might *NOT* want a literary agent:
* you want to self publish
* you're not willing to compromise on your edits
* you don't think their expertise is worth 15% of your advance
I... can't think this way. Literary agents have been crucial to my career. 3/

So, how do you get a literary agent?
1. Have a finished, revised, edited, polished manuscript.
2. Write a query letter for your book
3. Send your query to agents who rep your genre and are open to submissions
4. Repeat steps 1-4 until you're offered representation. 4/

So, let's go through those four steps. First of all, you must have a finished, revised, edited, polished book, and it must be sellable. That is, you can't sell a 600k picture book or a 40k adult Fantasy, etc. You must read extensively in the genre you're writing. 5/

WORLD OF SANATAN DHARM...
@world_sanatan

EVOLUTION OF CROWNS

The ancient Indian kings called a head crown as a Mukut and it would mostly constitute of a golden ornamental headgear like an oval cap with gems.

Sometimes it would also include a halo circle to show the divinity of the king

1/7

As it was considered that kings were appointment by the gods themselves. Example the kings of mewar considered themselves to be the ‘Diwan of eklingji')

But in most cases very few Mukut with halo effect have been found.

2/7

Samudragupta in the gupta era coin. You can see the helmet like headwear on him.

Till gupta era the solid golden head wear was used in most days of the monarch.

But since the onset of 8th century it reduced in usage and was now used only as a ceremonial headwear.

3/7

Whereas earlier the Maharaja had to wear the mukut whenever his court was in session.

Still mukut was being used prominently for ceremonial activities till recent times.

Maharaj Dahir of Sindh👇

4/7

But as times past the style of headwear also changed.

The kings mostly wore turbans ordained with pearls and gems while rarely anyone wore a true Mukut after 16th century.

Portrait of Sri Krishna Dev Raya👇

5/7

David Rothkopf
@djrothkopf

Pretending that voting for Trump or denying climate change or suggesting the solution to every problem is more guns is a legitimate point of view, worthy of respect is not "how America works." It is how it dies.

People in a free society are entitled to any point of view no matter how obviously wrong or outlandish or destructive provided they do not impose their views on others.

But suggesting that something ignorant or divorced from reality warrants the same kind of treatment in public debate as something based in fact or at least credible is absurd and when done on behalf of a society in public media or academic settings it is self-destructive.

We would not grant media coverage or much bandwidth at all to a group that argued that unicorns exist or that there was a pot of gold at the end of the rainbow. Yet views like denying climate change or basing policy decisions on sweeping, obvious lies, are just as unsound.

Somewhere, somehow, judgments must be made. Some behaviors are wrong and must be condemned. Someone must challenge lies and demand facts. Coddling people who embrace idiocies does not help them no matter how loudly they demand to be coddled.