I've also listed out the key highlights of each tutorial so that it is easy for you decide which one to pick.
A list of my favourite tutorials for learning Python as a beginner.
🧵 👇🏻
I've also listed out the key highlights of each tutorial so that it is easy for you decide which one to pick.
https://t.co/sSN3jdxDwK
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
key highlights
- 17 part course
- Jupyter notebooks
- Free eBook included
Duration: 8 hrs
https://t.co/sJE9YxW1rK
Key highlights
- Building a casic calculator
- Mad Libs Game
- Slightly advanced concepts like inheritance, Classes etc.
Duration: 4 hrs
https://t.co/0zdThohQHn
Key highlights
- Emoji Converter
- Projects: Automation, Machine Learning with Python and a website with Django
Duration: 5 hrs
https://t.co/AJw5QzWCsV
- Classes & Objects
- Working With Files
- Working With JSON
Duration: 1.5 hrs
https://t.co/CNJg8mJeR7
Key highlights
- Threading vs Multiprocessing
- Decorators
- Itertools
- Lambda Functions
- The Asterisk (*) Operator
- Shallow vs Deep Copying
Duration: 6 hrs
https://t.co/dWMU5P6E3K
You'll learn to build:
- Pong
- Snake
- Connect Four
- Tetris
- Online Multiplayer Game
Duration: 5 hrs
https://t.co/61hw8miHOo
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https://t.co/rgThYqo3Li
More from Pratham
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.
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This is NONSENSE. The people who take photos with their books on instagram are known to be voracious readers who graciously take time to review books and recommend them to their followers. Part of their medium is to take elaborate, beautiful photos of books. Die mad, Guardian.
THEY DO READ THEM, YOU JUDGY, RACOON-PICKED TRASH BIN
If you come for Bookstagram, i will fight you.
In appreciation, here are some of my favourite bookstagrams of my books: (photos by lit_nerd37, mybookacademy, bookswrotemystory, and scorpio_books)
Beautifully read: why bookselfies are all over Instagram https://t.co/pBQA3JY0xm
— Guardian Books (@GuardianBooks) October 30, 2018
THEY DO READ THEM, YOU JUDGY, RACOON-PICKED TRASH BIN
If you come for Bookstagram, i will fight you.
In appreciation, here are some of my favourite bookstagrams of my books: (photos by lit_nerd37, mybookacademy, bookswrotemystory, and scorpio_books)