I still remember how I wrote my first piece of code 6 years and all the amazing and cool things I've been able to do with it ever since.
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This is a step-by-step guide on getting started with Python as a total beginner.
(includes free resources and everything else you need to get started)
🧵👇
I still remember how I wrote my first piece of code 6 years and all the amazing and cool things I've been able to do with it ever since.
(2 / 24)
Don't expect to make AAA games or state of the art machine learning models in a week.
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With all that being said, let's dive straight in.
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Linux and macOS users can skip this step because they come pre-installed with Python.
Download link: https://t.co/KSZ4Qd6CNk
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Make sure to Add python to path by checking this option 👇
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We'll be installing VS-Code, one of the best code editors out there and it's free!
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🔗https://t.co/0cN2JyM2di
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🔗https://t.co/eijcOcz42c
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- Printing statements
- Variables
- Operators
- Conditions
- Functions
- Loops
Let's take a closer look.
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You can 'print' or output in Python using the print() function.
print('Hello World') will give you an output of `Hello World`
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These store certain values that can change.
For example, You can declare a variable 'x' with a certain value.
x = 9 [Here 9 is assigned to varaiable x]
y = 'Hello World' ['Hello World' is assigned to y]
x = 8 [x has been updated to a new value which is 8]
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These carry out arithmetic operations in Python
+ : Addition
- : Subtraction
* : Multiplication
/ : Divide
% : Modulus (Remainder after dividing)
** : Exponents
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They look like this 👇
a = 33
b = 200
if b > a:
print("b is greater than a")
else:
pass
Think of it as telling Python to do something based on conditions: if this is true, do this; else do something different.
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These are basically blocks of code that can be run when you call them. This helps us write code more efficiently.
In Python, you can make functions using the def keyword.
def myFunction():
print("Hello")
myFunction()
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These essentially run a piece of code over and over again until a certain condition is met.
There are 2 types of loops in Python:
- While loops
- For loops
Let's take a look at them.
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i = 1
while i < 6: //While i is less than 6
print(i) // do
i += 1 //this
The output is :
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fruits = ["apple", "banana", "cherry"]
for fruit in fruits:
print(x)
The output:
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'fruit' is the above loop is a temporary variable. It gets a value from the list called 'fruits' starting from "apple" then to "banana" and then "cherry".
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I have even more threads for further steps in Python coming up, stay tuned.
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Incredible text-based tutorials: https://t.co/qRvZNItSM2
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This course on Traversy Media's channel is a great next step for taking your python skills to the next level!
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This is probably the most underrated resource for learning python.
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More from Pratham Prasoon
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 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?
— Pratham (@PrasoonPratham) February 13, 2021
Here's everything you need to get started.
\U0001f9f5\U0001f447
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
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.
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?
— Pratham Prasoon (@PrasoonPratham) February 13, 2021
Here's everything you need to get started.
\U0001f9f5\U0001f447
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.
More from Tech
On press call, Zuckerberg says FB users "naturally engage more with sensational content" that comes close to violating its rules. Compares it to cable TV and tabloids, and says, "This seems to be true regardless of where we set our policy lines."
Zuckerberg says FB is in the process of setting up a "new independent body" that users will be able to appeal content takedowns to. Sort of like the "Facebook Supreme Court" idea he previewed earlier this year.
Zuckerberg: "One of my biggest lessons from this year is that when you connect more than 2 billion people, you’re going to see the good and bad of humanity."
This is how Facebook says it's trying to change the engagement pattern on its services. https://t.co/3p0PGc912o
.@RebeccaJarvis asks Zuckerberg if anyone is going to lose their job over the revelations in the NYT story. He dodges, says that personnel issues aren't a public matter, and that employee performance is evaluated all the time.
Zuckerberg says FB is in the process of setting up a "new independent body" that users will be able to appeal content takedowns to. Sort of like the "Facebook Supreme Court" idea he previewed earlier this year.
Zuckerberg: "One of my biggest lessons from this year is that when you connect more than 2 billion people, you’re going to see the good and bad of humanity."
This is how Facebook says it's trying to change the engagement pattern on its services. https://t.co/3p0PGc912o
.@RebeccaJarvis asks Zuckerberg if anyone is going to lose their job over the revelations in the NYT story. He dodges, says that personnel issues aren't a public matter, and that employee performance is evaluated all the time.
THREAD: How is it possible to train a well-performing, advanced Computer Vision model 𝗼𝗻 𝘁𝗵𝗲 𝗖𝗣𝗨? 🤔
At the heart of this lies the most important technique in modern deep learning - transfer learning.
Let's analyze how it
2/ For starters, let's look at what a neural network (NN for short) does.
An NN is like a stack of pancakes, with computation flowing up when we make predictions.
How does it all work?
3/ We show an image to our model.
An image is a collection of pixels. Each pixel is just a bunch of numbers describing its color.
Here is what it might look like for a black and white image
4/ The picture goes into the layer at the bottom.
Each layer performs computation on the image, transforming it and passing it upwards.
5/ By the time the image reaches the uppermost layer, it has been transformed to the point that it now consists of two numbers only.
The outputs of a layer are called activations, and the outputs of the last layer have a special meaning... they are the predictions!
At the heart of this lies the most important technique in modern deep learning - transfer learning.
Let's analyze how it
THREAD: Can you start learning cutting-edge deep learning without specialized hardware? \U0001f916
— Radek Osmulski (@radekosmulski) February 11, 2021
In this thread, we will train an advanced Computer Vision model on a challenging dataset. \U0001f415\U0001f408 Training completes in 25 minutes on my 3yrs old Ryzen 5 CPU.
Let me show you how...
2/ For starters, let's look at what a neural network (NN for short) does.
An NN is like a stack of pancakes, with computation flowing up when we make predictions.
How does it all work?
3/ We show an image to our model.
An image is a collection of pixels. Each pixel is just a bunch of numbers describing its color.
Here is what it might look like for a black and white image
4/ The picture goes into the layer at the bottom.
Each layer performs computation on the image, transforming it and passing it upwards.
5/ By the time the image reaches the uppermost layer, it has been transformed to the point that it now consists of two numbers only.
The outputs of a layer are called activations, and the outputs of the last layer have a special meaning... they are the predictions!
