BC MACHINE LEARNING
Saved by @Alex1Powell

Everything you need to know about the math for machine learning as a beginner.

๐Ÿงต๐Ÿ‘‡

 Before diving into the math, I suggest first having solid programming skills.

For example๐Ÿ‘‡

(2 / 17)
In Python, these are the concepts which you must know:

- Object oriented programming in Python : Classes, Objects, Methods
- List slicing
- String formatting
- Dictionaries & Tuples
- Basic terminal commands
- Exception handling

(3 / 17)
If you want to learn python, these courses are freecodecamp could be of help to you.

๐Ÿ”—Basics: youtube .com/watch?v=rfscVS0vtbw
๐Ÿ”—Intermediate :youtube .com/watch?v=HGOBQPFzWKo

(4 / 17)
You need to have really strong fundamentals in programming, because machine learning involves a lot of it.

It is 100% compulsory.

(5 / 17)
Another question that I get asked quite often is when should you start learning the math for machine learning?

(6 / 17)
Math for machine learning should come after you have worked on some projects, doesn't have to a complex one at all, but one that gives you a taste of how machine learning works in the real world.

(7 / 17)
Here's how I do it, I look at the math when I have a need for it.

For instance I was recently competing in a kaggle challenge.

(8 / 17)
I was brainstorming about which activation function to use in a part of my neural net, I looked up the math behind each activation function and this helped me to choose the right one.

(9 / 17)
The topics of math you'll have to focus on
- Linear Algebra
- Calculus
- Trigonometry
- Algebra
- Statistics
- Probability

Now here are the math resources and a brief description about them.

(10 / 17)
Neural Networks
> A series of videos that go over how neural networks work with approach visual, must watch

๐Ÿ”—youtube. com/watch?v=aircAruvnKk&list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi

(11 / 17)
Seeing Theory
> This website gives you an interactive to learn statistics and probability

๐Ÿ”—seeing-theory. brown. edu/basic-probability/index.html

(12 / 17)
Gilbert Strang lectures on Linear Algebra (MIT)
> They're 15 years old but still 100% relevant today!
Despite the fact these lectures are for freshman college students ,I found it very easy to follow.

๐Ÿ”—youtube. com/playlist?list=PL49CF3715CB9EF31D

(13 / 17)
Essence of Linear Algebra
> A beautifully crafted set of videos which teach you linear algebra through visualisations in an easy to digest manner

๐Ÿ”—youtube. com/watch?v=fNk_zzaMoSs&list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab

(14 / 17)
Khan Academy
>The resource you must refer to when you forget something or want to revise a topic.

๐Ÿ”—khanacademy. org/math

(15 / 17)
Essence of calculus
> A beautiful series on calculus, makes everything seem super simple

๐Ÿ”—youtube. com/watch?v=WUvTyaaNkzM&list=PL0-GT3co4r2wlh6UHTUeQsrf3mlS2lk6x

(16 / 17)
The math for Machine learning e-book
> This is a book aimed for someone who knows a decent amount of high school math like trignometry, calculus etc.

I suggest reading this after having the fundamentals down on khan academy.

๐Ÿ”—mml-book. github .io

(17 / 17)

More from Pratham Prasoon

Pratham Prasoon
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.

๐Ÿงต๐Ÿ‘‡

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
MACHINE LEARNING
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.
๐Ÿงต๐Ÿ‘‡

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 learning๐Ÿ‘‡

- 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
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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.

๐Ÿงต ๐Ÿ‘‡๐Ÿป

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 ๐Ÿ‘‡๐Ÿป

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 ๐Ÿ‘‡๐Ÿป


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 ๐Ÿ‘‡๐Ÿป


You will be constantly be working on multiple packages which specific python version requirements ๐Ÿ

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 Prasoon
Pratham Prasoon
@PrasoonPratham
Which libraries do you really need to get started with Machine Learning and why?

๐Ÿงต๐Ÿ‘‡

First and foremost, make sure that you have nailed the fundamental concepts of Python because machine learning requires a lot of programming!

(2 / 19)

If you know these topics, then you are good to go with machine learning in Python

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

(3 / 19)

Now, let's understand what popular python machine learning libraries do.

We will talk about๐Ÿ‘‡
- TensorFlow (+ Keras)
- PyTorch
- Pandas
- Numpy
- Matplotlib
- SciKit Learn
- Seaborn

(4 / 19)

Now let's cover the libraries that you have to learn (at least the basics) for machine learning

1. Pandas

Pandas is a python library that allows you to store and read data from spreadsheets ( .csv, .xlsv files ) in structures called Dataframes.

(5 / 19)
MACHINE LEARNING
Pratham
Pratham
@PrasoonPratham
I remember how hard it was to find resources for machine learning a couple of years ago.

Now we have so many of them, its impossible for you to not find what you're looking for.

Here are some of them ๐Ÿงต

1๏ธโƒฃ Kaggle

My go to place for finding datasets and code snippets, also a great place for discussions.


2๏ธโƒฃ Papers with code

A collection of the latest and greatest research papers and the best part, a github repository with the code is included!


3๏ธโƒฃ Kdnuggets

Guides, tutorials and articles on everything AI, Analytics, Big Data, Data Mining, Data Science, and Machine Learning.


4๏ธโƒฃ Towards Data Science

A blog about data science with accessible and well written articles.
CODING

More from Machine learning

Abhishek Thakur
Abhishek Thakur
@abhi1thakur
In this thread, I will tell you how to learn python for data science in 1 hour ๐Ÿ‘‡ 1/N

It's not possible 2/N

It's not possible 3/N

It's not possible 4/N

It's not possible 5/N
MACHINE LEARNING
Jan Giacomelli
Jan Giacomelli
@jangiacomelli
๐Ÿค” Python decorators

What are they? How do you use them?

๐Ÿงต Let's find out ๐Ÿ‘‡

1๏ธโƒฃ 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


2๏ธโƒฃ 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


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


4๏ธโƒฃ 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.
MACHINE LEARNING
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Pratham Prasoon \U0001f680
Pratham Prasoon ๐Ÿš€...
@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)
๐Ÿงต๐Ÿ‘‡


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 here๐Ÿ‘‡
๐Ÿ”—//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 YouTube๐Ÿ‘‡

Machine Learning foundations course
๐Ÿ”—//youtu.be/_Z9TRANg4c0

Code๐Ÿ‘‡
๐Ÿ”—//colab.research.google.com/github/PrasoonPratham/Kaggle/blob/main/MNIST.ipynb

(5 / 22)
MACHINE LEARNING
Santiago
Santiago
@svpino
For a long time, I didn't understand how to use Virtual Environments in Python ๐Ÿ.

If this is just, let's end it here and now: ๐Ÿงต๐Ÿ‘‡

[2] Virtual Environments let you deal with the dependencies that your code has with external Python libraries.

It avoids having conflicts when your projects depend on different versions of the same library.

๐Ÿ‘‡

[3] Let's imagine that you are building your first Python project and you install the "requests" library:

pip install requests

You get version 2.24.0 installed in your system.

๐Ÿ‘‡

[4] A month later, you decide to work on your second project. It also needs the "requests" library.

But the latest version is not 2.24.0 anymore.

Now version 3 is available, and that's the one you want to use!

๐Ÿ‘‡

[5] You could upgrade your entire system to version 3, but then you'll be potentially breaking the first project you built that depends on 2.24.0!

Can you imagine this happening on a server with many more applications running?

๐Ÿ‘‡
MACHINE LEARNING
Madison Kanna
Madison Kanna
@Madisonkanna
With hard work and determination, anyone can learn to code.

Hereโ€™s a list of my favorites resources if youโ€™re learning to code in 2021.

๐Ÿ‘‡

1. freeCodeCamp.

Iโ€™d suggest picking one of the projects in the curriculum to tackle and then completing the lessons on syntax when you get stuck. This way you know *why* youโ€™re learning what youโ€™re learning, and you're building things

2. https://t.co/7XC50GlIaa is a hidden gem. Things I love about it:

1) You can see the most upvoted solutions so you can read really good code

2) You can ask questions in the discussion section if you're stuck, and people often answer. Free

3. https://t.co/V9gcXqqLN6 and https://t.co/KbEYGL21iE

On stackoverflow you can find answers to almost every problem you encounter. On GitHub you can read so much great code. You can build so much just from using these two resources and a blank text editor.

4. https://t.co/xX2J00fSrT @eggheadio specifically for frontend dev.

Their tutorials are designed to maximize your time, so you never feel overwhelmed by a 14-hour course. Also, the amount of prep they put into making great courses is unlike any other online course I've seen.
MACHINE LEARNING

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Dr Catherine Pemble is...
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Right, screw it. Here's a thread on *that* FBLive by Alex Cairnie about #Govanhill. Lets do a watch-through shall we? (Mind, I'm a resident of Govanhill, and a sociologist. I'm also 5'3, and a visibly queer woman so if half his claims are true I should be living in terror)

00:30: Welcomes viewers and uses points out that his videos are only getting attention b/c they're 'horrific'. Directs folk to his Youtube page. So already clout hunting.

1:08: "I've been warned to stay out of Govanhill. I'm a marked man" (proceeds to use a beanie as a disguise)

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2:10 "Don't be under any illusion I'm only showing you the bad bits" - only shows you the bad bits.

3:45: He's had offers of help, but hes said no because hes not responsible for 'anybody elses safety' Good lord.

5:01: "Its not that bad. But its not all good either" -Correct

6:00: TW: child abuse - He starts claiming to have been contacted by a health professional and told about child abuse 'in the area'. Huge ethical issues here as the 'professional' who has 'been in the game a long time' is reporting to Facebook Dude and not authorities.
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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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Andrey \uf8ff Azimov
Andrey ๏ฃฟ Azimov
@AndreyAzimov
The best way to know if people like your product is NOT:

- Have a lot of emails in the waiting list
- Become #1 on PH
- Become #1 of HN or Reddit
- Have people that saing "I'll pay"
- Have a lot of free users

The best way to know if they're actually pay for it.

The only thing that matters is your product providing a value, and you can't know this until people will pay money for it.

We can have a first signal of a product/market fit after the launch by check how many sales we've got in the first 24h. Some scale:

200+ This has a high potential.
100+: This has a potential.
50+: Some people need it.
10+: People almost don't need it.
0+: People don't need it.

This is for a single time payment product. For a subscription probably it should be less because people hate subscription.

And obviously, you should have a lot of traffic like 3-5k+.

Here is a stat for my products (macOS apps) for the first 24h after the launch:
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๐™Ž๐™๐™–๐™ง๐™ž๐™ฃ๐™œ ๐™ข๐™ฎ ๐™ฌ๐™ž๐™จ๐™™๐™ค๐™ข ๐‘พ๐’๐’'๐’• ๐’ƒ๐’† ๐’”๐’–๐’“๐’‘๐’“๐’Š๐’”๐’†๐’… ๐’Š๐’‡ ๐’•๐’๐’Ž๐’๐’“๐’“๐’๐’˜ ๐’– ๐’“๐’†๐’‚๐’… ๐’•๐’‰๐’† ๐’”๐’‚๐’Ž๐’† ๐’”๐’•๐’–๐’‡๐’‡ ๐’Š๐’ 50๐’Œ ๐’˜๐’๐’“๐’Œ๐’”๐’‰๐’๐’‘ ๐’๐’“ ๐’”๐’๐’Ž๐’†๐’๐’๐’† ๐’Ž๐’‚๐’๐’‚๐’ˆ๐’Š๐’๐’ˆ ๐’š๐’๐’–๐’“ ๐’Ž๐’๐’๐’†๐’š ๐’˜๐’Š๐’•๐’‰ ๐’”๐’‚๐’Ž๐’† ๐’๐’๐’ˆ๐’Š๐’„
Simple and effective way 2 make Money


Idea 1:- Use pivot level like 14800 in case of nifty and sell 14800straddle monthly expiry (365+335) exit if nifty closes on daily basis below S1 or above R1

After closing below S1 if it closes above S1 next day or any day enter the same position again vice versa for R1

Idea2:- Use R1 and S1 corresponding strikes multiple
Incase of R1 15337 take 15300ce
N in case of S1 14221 use 14200pe
Sell both and hold till expiry or exit if nifty closes below S1 or above R1 around closing
If the same bounces above S1 and falls below R1 re-enfer same strikes

Use same criteria for nifty, usdinr and banknifty

(This is must)Use this margin rule for 1lot banknifty pair keep 4Lax margin
For nifty one lot keep 3Lax
For usdinr 100lots keep 4Lax

I bet you if you do this on consistent basis your ROI will be more than 70% on yearly basis.

Couldn't explain easier than this

Criticisms are most welcomed.
OPTIONSLEARNINGS , MONTHLY OPTIONS SELLING , OPTIONS LEARNING
History Of Rajputana
History Of Rajputana
@KshatriyaItihas
**Thread on Bravery of Sikhs**
(I am forced to do this due to continuous hounding of Sikh Extremists since yesterday)

Rani Jindan Kaur, wife of Maharaja Ranjit Singh had illegitimate relations with Lal Singh (PM of Ranjit Singh). Along with Lal Singh, she attacked Jammu, burnt - https://t.co/EfjAq59AyI


Hindu villages of Jasrota, caused rebellion in Jammu, attacked Kishtwar.

Ancestors of Raja Ranjit Singh, The Sansi Tribe used to give daughters as concubines to Jahangir.


The Ludhiana Political Agency (Later NW Fronties Prov) was formed by less than 4000 British soldiers who advanced from Delhi and reached Ludhiana, receiving submissions of all sikh chiefs along the way. The submission of the troops of Raja of Lahore (Ranjit Singh) at Ambala.

Dabistan a contemporary book on Sikh History tells us that Guru Hargobind broke Naina devi Idol Same source describes Guru Hargobind serving a eunuch
YarKhan. (ref was proudly shared by a sikh on twitter)
Gobind Singh followed Bahadur Shah to Deccan to fight for him.


In Zafarnama, Guru Gobind Singh states that the reason he was in conflict with the Hill Rajas was that while they were worshiping idols, while he was an idol-breaker.

And idiot Hindus place him along Maharana, Prithviraj and Shivaji as saviours of Dharma.
HISTORY