BC MACHINE LEARNING
Saved by @Alex1Powell

Here's what you'll hear when you first get into machine learning.

- Neural networks
- Loss
- Weights
- Biases
- Epochs
- Neurons
- Optimizers
...

It can get very confusing really fast!

Here are some of the terms you should know about.
(I wish I had this before)

🧵👇

 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.
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.
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.
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.
Once the dials are well tuned, you have a well trained neural network!

Each dial's numeric value is dependent on a "weight" and a "bias". The weight determines how important the neuron is and the bias make it flexible.
So here's a recap of what we've looked at so far:

The neural net is the brain of the machine learning model, the dials you have to adjust to make that neural net work are the neurons.
Let's move on🔥

👇
Each time data passes through the neural network, we get to know how wrong it is. The measure of how wrong a neural network is called the "loss". The neural network uses this thing called an "optmizer" to reduce "loss" and tries to get less wrong after each iteration.
The number of times the data passes through the neural net is called the "epoch".

That was a lot! Let's summarize👇
Neural Network: The brain of our machine learning model
Neuron : Each dial in a neural network
Weight : How important the neuron is
Bias : Flexibility of neuron
Epoch : Number of times the data passes through the neural network
Loss : How wrong the neural net is
Optimizer : Tries to reduce loss and make the neural net less wrong
Now some FAQs
> How to get started with machine learning?
Here👇

https://t.co/s5o54jt5oc
Which language to learn for machine learning?
> Python is the most common and well known, It would be my pick.

https://t.co/sey373KUpV
I don't have a powerful PC, how do I get into machine learning?
> You don't need one, use Google Colab.

https://t.co/ATd8YNZppb

More from Pratham Prasoon

Pratham
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?
ALL
Pratham
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


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
ALL
Advertisement
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
Pratham
@PrasoonPratham
A git cheat sheet for all your needs!

https://t.co/H7QdOrthwV
GIT
Pratham Prasoon
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


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.
MACHINE LEARNING

More from Machine learning

Prashant \U0001f4da
Prashant 📚
@capeandcode
Ever heard of Autoencoders?

The first time I saw a Neural Network with more output neurons than in the hidden layers, I couldn't figure how it would work?!

#DeepLearning #MachineLearning
Here's a little something about them: 🧵👇


Autoencoders are unsupervised neural networks whose architecture you can picture as two funnels connect from the narrow ends.

These networks are primary focus for compression tasks of data in Machine Learning.

We feed them the data so that they can learn the most important features, a smaller representation while keep the integrity of the data.

Later when someone needs, can just take that small representation and recreate the original, just like a zip file.📥

Being unsupervised, they require no labels.
Our inputs and outputs are same and a simple euclidean distance can be used as a loss function for measuring the reconstruction.

Of course, we wouldn't expect a perfect reconstruction.

We can think of an autoencoder having two components, encoder and decoder, represented by the below equations:

We are just trying to minimize the L here. All the backpropagation rules still hold.
MACHINE LEARNING
Santiago
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)
MACHINE LEARNING , TENSOR BASICS
Advertisement
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
Caio Rolla
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.
MACHINE LEARNING
Pratham Prasoon
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)
MACHINE LEARNING , PYTHONML

You May Also Like

Hypertroph | Fitness Coach
Hypertroph | Fitness C...
@CoachHypertroph
Transform your body in next 6 months.

People will charge INR 27,000+ for this course.

I am giving away the entire course for FREE:


Module 1:
Build your Fat Loss Diet Plan

· Step by Step Tutorial
· Length: 26

Module 2:
Learn how to easily track your calories/macros.

· Step by Step Tutorial
· Length: 17

Module 3:
Calculate how many weeks it will take to reach six pack.

. Math behind building six pack
· Length: 12

Module 4:
Learn how to Burn Belly Fat in 3 steps

· Science behind belly fat
· 100% Works
· Length: 15
WORKOUTS
Peter McCormack [Jan/3\u279e\u20bf \U0001f511\u220e]
Peter McCormack [Jan/3...
@PeterMcCormack
1/ So here is a thread on how I turned $32,000 into $1.2m and back to pretty much zero (once taxes are paid).

Just note, I am not bitter or salty in any way at all, the last 2 years have been an amazing ride - travelled the world, been wealthy, been poor.

2/ Dec '16, my advertising agency folded, I had a little bit of money left and I put $32k into Bitcoin and Ether. As it started to go up I diversified into everything, Monero, Dash, this that, any crap - even Ripplecoin. Everything just kept going up.

3/ By March I think I had around $300k and $500k by the summer. I used to take 25% out but towards the end of the summer I got greedy and put it all back in and by December it was $1.2m.

4/ Thinking I was an absolute genius I decided to start a bunch of businesses. As silly as it sounds I had this goal of making $5m as I wanted to buy Bedford Town Football Club and get them in the league, and as Crypto was going up forever I needed 6 months.

5/ So:
- Trading (income 1)
- Podcast (income 2)
- Mining (income 3)
- Mining pool (income 4)
- Consulting (income 5)

Yes - all of the above as a one-man army :)
LIFE
Advertisement
Anu Satheesh \U0001f1ee\U0001f1f3
Anu Satheesh 🇮🇳...
@AnuSatheesh5
Yoga Ramar Temple
#Nedungunam
#TamilNaduTemples 🚩

Yoga Ramar Temple is located near Thiruvannamalai. Shri Rama is seated with eyes closed, without any weapons. Mata Sita  pointing to the feet of Rama telling that  everyone is safe at his feet. Lakshmana standing near Shri Rama


Hanuman is seen chanting Vedas obediently sitting before Shri Rama.

Sthala Puranam says that, Sukabrahma Maharishi had been doing Tapasya here, for the darshan of Sri Rama. Prabhu Shri Ram, pleased with his tapasya, came here after Rama Ravana yudham. Since Rama was returning


after the war, he did not have any weapons with him.

Another gopuram called Kili Gopuram is there for Sukabrahma Maharishi. There is a hill nearby called Dheergachala. According to Sthala puranam, Sri Padham of Prabhu Rama are found on the top of the hill


It is said that this is the place where Shri Rama gave darshan to Suka Maharishi. Nedumgunam means which shows all qualities of Shri Rama who is Maryadha purushottam. Shri Ramanavami is very famous here.

Jai Sri Ram
🙏🕉🙏
ALL
Melissa (she/her)
Melissa (she/her)
@LiteraryMouse
In regards to the #CapitolCoup, I’m in a unique position. I monitored forums ahead of time and then was present for the coup itself.

These are my observations based on what I saw and the evidence that’s been collected so far. I reserve the right to adjust my analysis as needed.

Let’s talk about the organization of the coup first. Seeing some people insist that the coup must have been highly planned and coordinated.

Yes and no. This was a #StochasticCoup. We’ll see little evidence of direct communication between Trump and the insurrectionists.

Within the insurrectionists, there was not one group that executed the storming of the Capitol.

Rather, there were a number of smaller groups working independently towards the same goal. I expect you’ll see little evidence that these various groups communicated with each other.

What you will see is detailed planning and coordination within these small groups.

Then there were the joyriders, those Trump supporters who weren’t directly involved in any plotting but who were more than happy to go along for the ride once the coup was in motion.

After four years, the insurrectionists were carefully attuned to Trump’s messaging.

Every tweet and statement of his was treated as marching orders and carefully dissected for meaning.

It’s why shutting down Trump’s Twitter account was so important.
POLITICS , INSURRECTIONISTS
Ethan \U0001f468\u200d\U0001f3a4
Ethan 👨‍🎤...
@Booligoosh
First update to https://t.co/lDdqjtKTZL since the challenge ended – Medium links!! Go add your Medium profile now 👀📝 (thanks @diannamallen for the suggestion 😁)


Just added Telegram links to https://t.co/lDdqjtKTZL too! Now you can provide a nice easy way for people to message you :)


Less than 1 hour since I started adding stuff to https://t.co/lDdqjtKTZL again, and profile pages are now responsive!!! 🥳 Check it out -> https://t.co/fVkEL4fu0L


Accounts page is now also responsive!! 📱✨


💪 I managed to make the whole site responsive in about an hour. On my roadmap I had it down as 4-5 hours!!! 🤘🤠🤘
MAKERS