BC MACHINE LEARNING

Saved by @CodyyyGardner

Pratham Prasoon
@PrasoonPratham 4 years, 5 months ago 950 views

Save to PDF Share See On Twitter

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

.. and instead creates a copy of the csv or database as a python array in the RAM.

We use Numpy in order to change the shape of the data we just pulled using Pandas, the arrays are converted to special numpy arrays which are much faster than Python's default ones.

(6 / 11)

Matplotlib is used to visualize data, bar graphs, line plots, pie charts... you get the point.

These are the frameworks that you will have to use extensively throughout your machine learning journey.

(7 / 11)

Now comes the tougher part, TensorFlow, Pytorch, Keras or Scikit learn? Or all? or neither?....

It depends on personal preference.

(8 / 11)

TensorFlow, Keras and Pytorch generally do the same thing in different syntax.

SciKit learn has a bunch of scientific tools which you might need here and there.

(9 / 11)

Here's what I suggest, try making a convolutionary neural network for the MNIST dataset with all of these and then decide which one is right for you.

I personally use TensorFlow + ScikitLearn, it might not work for you.

(10 / 11)

More from Pratham Prasoon

Pratham
@PrasoonPratham

Everyone tells you how important math is in machine learning.

But I believe that if you want to learn machine learning today, there are things more important than math which very few people will tell you about.

Here are 5 of them.

🧵 👇🏻

The field of machine learning has been very academic which is why there is so much emphasis on learning math for it.

But, today with the frameworks that we have, not knowing how to multiply matrices is far less of an issue than knowing how to use the tools in this list 👇🏻

Yes, I know; you have R, Julia, and whatnot for machine learning but as of today, Python is the industry standard.

Get your data structures and algorithms right in Python because you will need them, here are some concepts worth learning 👇🏻

Let's say you're building the next big GPT-3 powered app that's going to take over the world.

You add a new feature to your app but it breaks the entire thing, what do you do now?

Learn Git, the ultimate version control tool.

I use this cheat sheet for all my git needs 👇🏻

You will be constantly be working on multiple packages which specific python version requirements 🐍

Virtual environments like Anaconda or Poetry will make this process much easier for you.

Who likes to see broken dependencies while running code?

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

Advertisement

Pratham Prasoon
@PrasoonPratham

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)

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.

Pratham
@PrasoonPratham

A list of my favourite tutorials for learning Python as a beginner.

🧵 👇🏻

All the tutorials below include the basics like installation, variables etc.

I've also listed out the key highlights of each tutorial so that it is easy for you decide which one to pick.

Before going through these tutorials I would highly suggest you to go through this thread if you are a complete

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

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

The Full Python Course from learn with Python with Rune

key highlights
- 17 part course
- Jupyter notebooks
- Free eBook included

Duration: 8

The Python Beginner's course on FreeCodeCamp's YouTube Channel.

Key highlights

- Building a casic calculator
- Mad Libs Game
- Slightly advanced concepts like inheritance, Classes etc.

Duration: 4

More from Machine learning

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)

Jan Giacomelli
@jangiacomelli

🤔 Python decorators

What are they? How do you use them?

🧵 Let's find out 👇

1️⃣ Decorator is a function or a class that wraps another function or class modifying its behavior.

So how does that work?

The first thing to know is that everything in Python is an object - functions too

2️⃣ That means they can be passed to another function as an argument or returned from a function

Functions that take other functions as an argument are called higher-order functions

3️⃣ In Python, you can define a function inside other function - such functions are called inner functions

4️⃣ To create a decorator you just need to apply all of that together

log_enter_leave is a decorator.

my_function is the function.

To alter my_function's behavior we reassign it applying log_enter_leave decorator.

Advertisement

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.

Pratham Prasoon
@PrasoonPratham

There are several skills needed for learning machine learning that no one talks about.

Here are some of them.
(from what I've learned over the past two years)
🧵👇

This thread aims to introduce to you some of the skills often ignored for learning machine learning but are actually very important.

These skills will enable you to learn concepts quickly and more efficiently in this field.

(2 / 9)

1⃣ Reading

Probably one of the most underrated skills on this list.

In machine learning, you HAVE to read a lot of articles, papers, documentation, and whatnot.

It is mostly due to the theoretical nature of this field that reading is an important skill to have.

(3 / 9)

2⃣ Strong fundamentals in programming

Machine learning is just a lot of programming mixed with math and data.

Having clear programming fundamentals is crucial for this field.

I highly suggest you learn about these if you are using Python for machine learning.👇

(4 / 9)

- Object oriented programming in Python :Classes, Objects, Methods
- Lists & List functions
- Dunder Methods
- List comprehension
- List slicing
- String formatting
- List, Dictionaries & Tuples
- *args,**kwargs

(5 / 9)

You May Also Like

Jig's Patel
@jigspatel1988

Thread on
"Intraday Banknifty Strangle based on OI data"

(System already shared, today just share few examples)
(1/n)

-Trade timing after 9:45

-Check Banknifty change in OI data at 9:45, and identify the highest OI built up in call side and put side

-We will sell both strikes with combined premium as SL on both legs.
(2/n)

28th June 2021

BN open-35440
At 9:45 trading at 35350
Highest OI in call side at 35500 CE and 35000 at put side
Strike selection 35500 CE- 35000 PE
(3/n)

29th June 2021

BN open-35323

At 9:45 trading at 35112

Highest OI in call side at 35300 CE and 35000 at put side

Strike selection 35300 CE (232) - 35000 PE (150) Combined premium 382 , Both legs SL 382
(4/n)

30th June 2021

BN open-35030

At 9:45 trading at 35002

Highest OI in call side at 35000 CE and 35000 at put side

Strike selection 35000 CE(176)- 35000 PE(213) Combined premium 389 , Both legs SL 389
(5/n)

$Em\U0001f383jipedia \U0001f4d9$

Em🎃jipedia 📙...
@Emojipedia

✨📱 iOS 12.1 📱✨
🗓 Release date: October 30, 2018
📝 New Emojis: 158
https://t.co/bx8XjhiCiB

New in iOS 12.1: 🥰 Smiling Face With 3 Hearts https://t.co/6eajdvueip

New in iOS 12.1: 🥵 Hot Face https://t.co/jhTv1elltB

New in iOS 12.1: 🥶 Cold Face https://t.co/EIjyl6yZrF

New in iOS 12.1: 🥳 Partying Face https://t.co/p8FDNEQ3LJ

Advertisement

$Kitze @ \U0001f1e9\U0001f1ea\ufe0f$

Kitze @ 🇩🇪️...
@thekitze

To people who are under the impression that you can get rich quickly by working on an app, here are the stats for https://t.co/az8F12pf02

📈 ~12000 vistis
☑️ 109 transactions
💰 353€ profit (285 after tax)

I have spent 1.5 months on this app. You can make more $ in 2 days.

🤷‍♂️

I'm still happy that I launched a paid app bcs it involved extra work:

- backend for processing payments (+ permissions, webhooks, etc)
- integration with payment processor
- UI for license activation in Electron
- machine activation limit
- autoupdates
- mailgun emails

etc.

These things seemed super scary at first. I always thought it was way too much work and something would break. But I'm glad I persisted. So far the only problem I have is that mailgun is not delivering the license keys to certain domains like https://t.co/6Bqn0FUYXo etc. 👌

omg I just realized that me . com is an Apple domain, of course something wouldn't work with these dicks

$FT Trading\u2503Stock Trader$

FT Trading┃Stock Trade...
@FT__Trading

Ever wonder how traders get in stocks before they explode? 🧐

Or find options that move 1,000% in a single day/week?🤯

I made a thread going over exactly how I find these stocks BEFORE they take off 🚀
👇👇👇

So, let's start with the software I use…

Finviz!! Finviz is a free website that I use to scan for stocks.

They have a lot of other cool features as well, but I only use their scanner.
👇

Head on over to finviz and go to the screener

Click on the “All” tab on the top and put in the criteria in the next tweet
👇

This is the first scan that I use for bullish swing setups
✅Quarter +10%
✅Week Down
✅Vol over 400k
✅Optionable
✅Price > $20
👇

The next scan I use is the opposite of the first one.

Simply change:
✅Quarter +10% to -10%
✅Week Down to Week up

This is my bearish scan for swing setups. 👇

Anshul Pandey
@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.