BC MACHINE LEARNING
Saved by @CodyyyGardner

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)
The two most common misconceptions about getting started with machine learning are:

- You need PhD math
- You need a really expensive computer

Math is important but it is not for getting started with machine learning, it can come later on.

(6 / 14)
You do not need any those of those to get started, here's what you really need:

- A computer or smartphone
- Knowing how to program decently well
- Hunger for learning

(7 / 14)
Most web developers pretty much have all of these under their belt!
What you really need are some resources and guidance.

Let's start with the language you should use for machine learning

(8 / 14)
The JavaScript machine learning ecosystem is quite mature enough yet, which is why I will suggest you to learn Python.

Not to mention that getting started with Python will be a piece of cake if you already know JavaScript.

(9 / 14)
This course by FreeCodeCamp will help you get started with Python.

👉www.​youtube.​com/watch?v=rfscVS0vtbw

(10 / 14)
It is highly recommended that you use Google colab (an online IDE) for your machine learning code. You'll get a free GPU and you will not have to download large libraries onto your computer, everything stays in the cloud.

👉colab.​research.​google.​com

(11 / 14)
Kaggle is the best place to look for datasets and competitions which you can participate in to take your machine learning skills to the next level.

This thread will guide you on how you can get started with one such kaggle challenge

(12 / 14)

https://t.co/yo2W7nWBj2
You've probably learnt a lot by now and you should be proud about it, however there is still lots to learn.

- Visualising data using matplotlib
- Activation functions
- Decision Trees
....

(13 / 14)

More from Pratham Prasoon

Pratham
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
ALL
Pratham Prasoon
Pratham Prasoon
@PrasoonPratham
Here's everything you need to know about the math for machine learning.

(+ free resources )
🧵👇

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

For example👇

(2 / 18)

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 / 18)

If you want to learn those concepts for python, these courses are freecodecamp could be of help to you.

🔗Basics:youtube∙com/watch?v=rfscVS0vtbw
🔗Intermediate :youtube∙com/watch?v=HGOBQPFzWKo

(4 / 18)


👉You need to have really strong fundamentals in programming, because machine learning involves a lot of it.

It is 100% compulsory.

(5 / 18)
MACHINE LEARNING
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Pratham Prasoon
Pratham Prasoon
@PrasoonPratham
This is how I got three job offers as a 16-year-old high school student.

( and why I rejected them )
🧵👇

June 2020.

I receive a DM from a college student in California. The message read something like this "Hey Pratham, I am one of the co-founders of XYZ Inc, a robotics company, we are looking to add enthusiastic people to our team, would you be interested?"

(2 / 11)

It was the first time I had ever been offered a job, so I said Yes! (I did reject it later)

There were a couple of interview rounds I had to go through. None of them included technical questions, which was interesting.

(3 / 11)

After the first interview, I saw the list of the roles I could apply for. I realized how little I knew, terms like "Ui/UX, ROS(Robot operating system)", at that time, I was overwhelmed.

(4 / 11)

I knew that this wasn't a job for me. I decided that I would reject this job role even if I cleared the second round, which I ended up doing.

(5 / 11)
LIFE
Pratham Prasoon
Pratham Prasoon
@PrasoonPratham
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
MACHINE LEARNING
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)
MACHINE LEARNING , PYTHON USEFUL

More from Machine learning

Pratham Prasoon
Pratham Prasoon
@PrasoonPratham
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.
MACHINE LEARNING
Jan Giacomelli
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.
MACHINE LEARNING
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Quant@Python
Quant@Python
@BeingHorizontal
Thread for beginners; How to learn machine learning.

Let’s start with something really simple and useful not just for Machine Learning.

Start with a Python library called pandas. It’s a huge library but it's mostly fun for traders because it's kind of rewarding to learn each function and how it gonna affect the way you handle the financial data.

Then learn some basic stuff about Python library called NumPy. Pandas is built on NumPy. Numpy is huge, you just need to understand some basic NumPy functions like NumPy shapes and NumPy arrays

If you understand pandas then you will understand NumPy arrays and shapes easily. Side note: Numpy shapes gonna play an important part in the deep learning model called LSTM - mainly used for time-series analysis(such as financial data) and Natural Language Processing (NLP)
MACHINE LEARNING
Marcus Mengs
Marcus Mengs
@mame82
Okay, doing my first baby steps with r2frida (which combines the power of @radareorg and @fridadotre).

Gonna share my progress in this thread (live, so keep calm).

The goal: Runtime inspection of data sent out by TikTok !!before!! it gets encrypted

1/many

First of all, we do not start from zero. I got some prior knowledge from past reversing attempts and want to share some important facts.

TikTok's (log data) encryption is accomplished by a native library. The Android Java code just serves as proxy function to the native function

The decompiled code for the respective native JNI function of an older TikTok version looks something like this, but in this example I use the most current TT version (no statical analysis done, yet)


In case you never reversed native libraries which were build to interface with Android Java layer via JNI, I highly suggest the entry level introduction on the topic by @maddiestone

Before we start, I want to pinpoint some important aspects (which are also covered by Maddie's videos).

1) Unlike raw C-functions, JNI functions like the one showcased above, receive pointers to complex Java objects .

F.e. a function receiving a String on the Java layer...
MACHINE LEARNING
Santiago
Santiago
@svpino
The 8-step quick-start guide to learn Machine Learning.

🧵👇

1⃣ Start with Python 🐍

Yes, you can do other languages, but Python is by far the most straightforward option.

👇

2⃣ Get familiar with numpy, pandas, and matplotlib

These three libraries are probably the most common Python libraries you'll have to use every day.

(Even if you don't end up doing machine learning, these libraries are awesome and useful.)

👇

3⃣ Start using notebooks

Look into Jupyter or Google Colab.

Notebooks are essential for data scientists and machine learning practitioners. Most of the code you'll read and write will be in notebooks.

👇

4⃣ Find a problem (already solved)

In my opinion, the best way to start is by working through a problem —especially when you can learn from its solution.

Start with something simple. I usually recommend "Titanic" from Kaggle.

👇
MACHINE LEARNING , STARTING MACHINE LEARNING

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This day was inevitable. Indian Muslims always lived in La La Land. They bad mouthed real well wishers & slept with the enemy who never considered them as part of them. In Gulf, Indian Muslims were busy with Javed Akhtar & Sonu Nigam. Never interacted with South Asian diaspora

Now when Indian Muslims are thrown to wolves it’s Pakistani & Bangladeshi Muslims with whom they kept distance are the only ones feeling their pain. None of the people who they invited for Eid Milan. Qawali & Mushaira are there for them. Such people invoke wrath upon themselves

Indian Muslims never spoke for Kashmiri Muslims. Distancing from separatist was understandable but we never even bothered to highlight their human rights violation & rapes carried out by forces. We could have sent them humanitarian help we didn’t. Our silence made us complicit.

When Sania Mirza married Shoaib Malik it was something legal. A Muslim married another Muslim. Entire Hindutva media went after her. They launched a witch-hunt for months. No Indian Muslim stood by her. All were silent. Now days come when Muslims are arrested for marrying a Hindu

Indian Muslims particularly the elite downplayed communalism in India by saying it will pass or Hindu majority is good. Fringe are bad. They misguiding others. Muslims were always others. Indians were happy to see Muslims sing & dance & eat their food but never considered as own
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Billy Bostickson \U0001f3f4\U0001f441&\U0001f441 \U0001f193
Billy Bostickson 🏴👁&👁 ...
@BillyBostickson
Tip from the Monkey
Pangolins, September 2019 and PLA are the key to this mystery
Stay Tuned!


1. Yang


2. A jacobin capuchin dangling a flagellin pangolin on a javelin while playing a mandolin and strangling a mannequin on a paladin's palanquin, said Saladin
More to come tomorrow!


3. Yigang Tong
https://t.co/CYtqYorhzH
Archived: https://t.co/ncz5ruwE2W


4. YT Interview
Some bats & pangolins carry viruses related with SARS-CoV-2, found in SE Asia and in Yunnan, & the pangolins carrying SARS-CoV-2 related viruses were smuggled from SE Asia, so there is a possibility that SARS-CoV-2 were coming from
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Brianne Kimmel \U0001f4ac
Brianne Kimmel 💬...
@briannekimmel
Shocking fact: Millennial men are less likely to work than any other age and gender demographic in America.

Today, there are 500,000 young men missing from the U.S. workforce.

Research suggests video games & improved leisure tech plays a role in the problem. 👇 Thread:

Following the 2007 to 2009 recession, 25 to 34 year old men exited high school with fewer middle-skill job opportunities than years prior.

During this time, we saw an increased number of men living with parents & choosing unemployment over lower paying jobs.

It's estimated that 24M millennials live w/ their parents.

1 in 4 living in their parents’ home neither go to school nor work.

What's more surprising? 9 in 10 who lived with their parents a year ago are still living there w/ no plans to leave.

Economists are calling millennial men a lost generation.

According to economist David Dorn:

“If you get to the point where you’re turning 30, you’ve never held a real job and you don’t have a college education, then it is very hard to recover at that point.”

Economists suggest this choosiness is a generational trait.

Forbes interview w/ a high school educated man:

"I’m very quick to get frustrated when people refuse to pay me what I’m worth."
“People feel that they have choice nowadays, and they
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KrishnaLeela
KrishnaLeela
@Talesofkrishna
🌿𝑻𝒉𝒆 𝒔𝒕𝒐𝒓𝒚 𝒐𝒇 𝒂 𝑺𝒕𝒂𝒓 : 𝑫𝒉𝒓𝒖𝒗𝒂 & 𝑽𝒊𝒔𝒉𝒏𝒖

Once upon a time there was a Raja named Uttānapāda born of Svayambhuva Manu,1st man on earth.He had 2 beautiful wives - Suniti & Suruchi & two sons were born of them Dhruva & Uttama respectively.
#talesofkrishna https://t.co/E85MTPkF9W


Now Suniti was the daughter of a tribal chief while Suruchi was the daughter of a rich king. Hence Suruchi was always favored the most by Raja while Suniti was ignored. But while Suniti was gentle & kind hearted by nature Suruchi was venomous inside.
#KrishnaLeela


The story is of a time when ideally the eldest son of the king becomes the heir to the throne. Hence the sinhasan of the Raja belonged to Dhruva.This is why Suruchi who was the 2nd wife nourished poison in her heart for Dhruva as she knew her son will never get the throne.


One day when Dhruva was just 5 years old he went on to sit on his father's lap. Suruchi, the jealous queen, got enraged and shoved him away from Raja as she never wanted Raja to shower Dhruva with his fatherly affection.


Dhruva protested questioning his step mother "why can't i sit on my own father's lap?" A furious Suruchi berated him saying "only God can allow him that privilege. Go ask him"
RELIGION
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
🙏🕉🙏
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