BC MACHINE LEARNING

Saved by @CodyyyGardner

Pratham Prasoon
@PrasoonPratham 5 years, 5 months ago 1337 views

Save to PDF Share See On Twitter

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

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

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)

Advertisement

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)

Pratham
@PrasoonPratham

This is a beginner's guide on mining cryptocurrencies.

🧵 👇🏻

Mining 101

Typically, when you transfer money using a service like Paypal, they take a small cut for facilitating the exchange.

In cryptocurrencies, people like you and me act as Paypal and facilitate exchanges of cryptocurrency. We get a cut for this just like Paypal did.

In order to make these transactions happen, our computers need to do some calculations which requires a lot of computational power.

A GPU or a Graphics Processing Unit which is typically marketed for gaming workloads can be used to mine cryptocurrencies.

Why do you need a GPU?

Today, there are so many miners that the "difficulty" of mining cryptocurrencies has skyrocketed, which basically means it takes a lot of computational power to mine crypto which GPUs can provide and CPUs cannot.

(❗ This is an oversimplification)

If you are interested in the inner workings of how blockchain and cryptocurrency, then I highly suggest that you read this thread by @oliverjumpertz

What actually is a Blockchain?

Bitcoin is breaking record after record, but there must be more to the technology than just crypto, or not? Well, we can take a look at the underlying technology first to understand what it actually provides to us.

\U0001f9f5\u2b07\ufe0f
— Oliver Jumpertz (@oliverjumpertz) February 16, 2021

$Pratham Prasoon \U0001f680$

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)

More from Machine learning

$Unknown \U0001f464$

Unknown 👤
@console_404

10 PYTHON 🐍 libraries for machine learning.

Retweets are appreciated.
[ Thread ]

1. NumPy (Numerical Python)

- The most powerful feature of NumPy is the n-dimensional array.

- It contains basic linear algebra functions, Fourier transforms, and tools for integration with other low-level languages.

Ref: https://t.co/XY13ILXwSN

2. SciPy (Scientific Python)

- SciPy is built on NumPy.

- It is one of the most useful libraries for a variety of high-level science and engineering modules like discrete Fourier transform, Linear Algebra, Optimization, and Sparse matrices.

Ref: https://t.co/ALTFqM2VUo

3. Matplotlib

- Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.

- You can also use Latex commands to add math to your plot.

- Matplotlib makes hard things possible.

Ref: https://t.co/zodOo2WzGx

4. Pandas

- Pandas is for structured data operations and manipulations.

- It is extensively used for data munging and preparation.

- Pandas were added relatively recently to Python and have been instrumental in boosting Python’s usage.

Ref: https://t.co/IFzikVHht4

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

Advertisement

Pratham Prasoon
@PrasoonPratham

Are you planning to learn to 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)

Santiago
@svpino

An introduction to one of the the most basic structures used in machine learning: a tensor.

🧵👇

Tensors are the data structure used by machine learning systems, and getting to know them is an essential skill you should build early on.

A tensor is a container for numerical data. It is the way we store the information that we'll use within our system.

(2 / 16)

Three primary attributes define a tensor:

▫️ Its rank
▫️ Its shape
▫️ Its data type

(3 / 16)

The rank of a tensor refers to the tensor's number of axes.

Examples:

▫️ The rank of a matrix is 2 because it has two axes.
▫️ The rank of a vector is 1 because it has a single axis.

(4 / 16)

The shape of a tensor describes the number of dimensions along each axis.

Example:

▫️ A square matrix may have (3, 3) dimensions.
▫️ A tensor of rank 3 may have (2, 5, 7) dimensions.

(5 / 16)

Kieran Snyder
@KieranSnyder

1 There's a chasm between an NLP technology that works well in the research lab and something that works for applications that real people use. This was eye-opening when I started my career, and every time I talk to an NLP engineer at @textio, it continues to strike me even now.

2 Research conditions are theoretical and/or idealized. A huge problem for so-called NLP or AI startups with highly credentialed academic founders is that they bring limited knowledge of what it takes to build real products outside the lab.

3 A product is ultimately a thing that people pay for - not just cool technology or user experience. But I’m not even talking about knowledge gaps in go-to-market work. I'm talking purely technical gaps: how you go from science project to performant + delightful user experience.

4 Most commoditized NLP packages solve well-understood problems in standard ways that sacrifice either precision or performance. In a research lab, this is not usually a hard trade-off; in general, no one is using what you make, so performance is less important than precision.

5 In software, when you’re making something for real people to use, these tradeoffs are a big deal. Especially if you’re asking those people to pay for what you’ve made (can’t get away from that pesky GTM thinking). They expect quality, which includes precision AND performance.

You May Also Like

Jaya_Upadhyaya
@Jayalko1

SRI BANASHANKARI AMMAN, BANGALORE
#bharatmandir

Located in Southern Bangalore, this is one of the most popular places of worship in Bangalore City.
Devoted to Devi Banashankari, this shrine is visited specially during Rahukala which is believed to be an unfavorable time.

Somanna Shetty, a great devotee of Devi, brought this murti from Badami’s Banshankari Amma Kshetram.
It is said that many years ago, three ladies visited this shrine and requested the pujari to conduct puja for them. Since it was the inauspicious rahu kaal, the pujari refused.

However, upon their insistence, he conducted the puja. When he returned with prasadam, the ladies vanished. This made the people believe that they were none other than the Devi herself. Since then, the people perform poojas here during the Rahukaal.
@GunduHuDuGa

People use lemons as a diya. Lemons are cut from the centre and their pulps are removed, for pouring oil in them.
It is strongly believed that Devi removes all the troubles from the life of her devotees during the Rahukala although it is considered inauspicious for any pooja.

Anu Satheesh
@AnuSatheesh5

Importance of Famous Payyannur Pavithra Mothiram or Ring

Payyanur Sri Subramanya Swami Temple 🚩
Kerala

Temple, constructed by Parasurama is known as the 'Pazhani' of Kerala.The place got its name from 'Payyante Ooru' where Payyan is another name by which Subramanya was called.

There are references about this temple in Brahmanda purana. Muni Garga mentions this temple and the place to the Pandavas when they were in Vanavasa. Temple was destroyed two times, once due to fire and then during the attack of Tipu Sultan.

Important tradition here is wearing of Pavithram by the temple priest. Pavithram is a sort of ring worn during performing Vedic rituals or during the "pithrubali". Usually worn while performing Tarpana or Shradham. The traditional Pavitram is usually made of Dharbha grass

Advertisement

raina douris
@RahRahRaina

fascinated by this man, mario cortellucci, and his outsized influence on ontario and GTA politics. cortellucci, who lives in vaughan and ran as a far-right candidate for the italian senate back in 2018 - is a major ford donor...

his name might sound familiar because the new cortellucci vaughan hospital at mackenzie health, the one doug ford has been touting lately as a covid-centric facility, is named after him and his family

but his name also pops up in a LOT of other ford projects. for instance - he controls the long term lease on big parts of toronto's portlands... where doug ford once proposed building an nfl stadium and monorail... https://t.co/weOMJ51bVF

cortellucci, who is a developer, also owns a large chunk of the greenbelt. doug ford's desire to develop the greenbelt has been

and late last year he rolled back the mandate of conservation authorities there, prompting the resignations of several members of the greenbelt advisory

Rudy Havenstein, liste...
@RudyHavenstein

I hate when I learn something new (to me) & stunning about the Jeff Epstein network (h/t MoodyKnowsNada.)

Where to begin?

So our new Secretary of State Anthony Blinken's stepfather, Samuel Pisar, was "longtime lawyer and confidant of...Robert Maxwell," Ghislaine Maxwell's Dad.

"Pisar was one of the last people to speak to Maxwell, by phone, probably an hour before the chairman of Mirror Group Newspapers fell off his luxury yacht the Lady Ghislaine on 5 November, 1991." https://t.co/DAEgchNyTP

OK, so that's just a coincidence. Moving on, Anthony Blinken "attended the prestigious Dalton School in New York City"...wait, what? https://t.co/DnE6AvHmJg

Dalton School...Dalton School...rings a

Oh that's right.

The dad of the U.S. Attorney General under both George W. Bush & Donald Trump, William Barr, was headmaster of the Dalton School.

Donald Barr was also quite a

Donald Barr had a way with words. pic.twitter.com/JdRBwXPhJn
— Rudy Havenstein, listening to Nas all day. (@RudyHavenstein) September 17, 2020

I'm not going to even mention that Blinken's stepdad Sam Pisar's name was in Epstein's "black book."

Lots of names in that book. I mean, for example, Cuomo, Trump, Clinton, Prince Andrew, Bill Cosby, Woody Allen - all in that book, and their reputations are spotless.

Seth Abramson
@SethAbramson

(THREAD) Pre-election Russia collusion may take down Trump. It's equally possible the Trumps' pre- and post-election collusion with Saudi Arabia, the UAE, and Israel will do it—a course of collusion also connected to the Kremlin. I explain here. I hope you'll read on and retweet.

1/ I must stress how unbelievably complex the "Grand Bargain" theory of the Trump-Russia case is—a different thing from saying it's not substantiated. It's substantiated in *almost every single particular*—it just *also* happens to be very confusing. Not byzantine—just confusing.

2/ The basics: Saudi Arabia, Israel, and the UAE all view Iran as their chief regional enemy. Iran is propped up by Russia. Therefore the Saudis, Israelis, and Emiratis all need a US government willing to find a way to get the Kremlin to *stop* supporting Iran in the Middle East.

3/ The best way to get Russia to stop supporting Iran—or reduce support—was/is to drop all sanctions on Russia over its 2014 annexation of Crimea, as that'd be worth *trillions* to the Kremlin over the next decade. Everyone knew that Clinton wouldn't do this—and that Trump would.

4/ Per the NYT, on August 3, 2016, Donald Trump Jr. met secretly at Trump Tower with a Saudi and Emirati emissary, George Nader, as well as an Israeli intelligence expert, Joel Zamel, with *significant* ties to both Israeli intelligence *and* Russian oligarchs allied with Putin.