All of this is based on my experience of successfully teaching 300+ students how to code using Python.
(2 / 19
Are you planning to learn Python for machine learning this year?
Here's everything you need to get started.
🧵👇
All of this is based on my experience of successfully teaching 300+ students how to code using Python.
(2 / 19
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)
- Basic terminal commands
- Basic arithmetic (+,-,/,*)
- Accepting user input
- For & While loops
- Exception handling
- If-Else statements
- Functions, modules & Imports
(4 / 19)
- Object oriented programming in Python:Classes, Objects, Methods
- PIP (Pypi)
- List slicing
- String formatting
- Dictionaries & Tuples
- Managing environments
- Dunder methods like __init__
(5 / 19)
- Lambda functions
- Built in libraries like CSV, requests, Sqlite
- Map and Filter
- *args and **kwargs
- Async
- Decorators
(6 / 19)
Let's tackle this issue.
(7 / 19)
- Anaconda for managing environments (different versions of Python)
- Python3
- Machine learning packages like Sckit learn and TensorFlow using pip when needed
(8 / 19)
MacOS: 🔗docs.anaconda.com/anaconda/install/mac-os/
Windows: 🔗docs.anaconda.com/anaconda/install/windows/
Linux: 🔗docs.anaconda.com/anaconda/install/linux/
(9 / 19)
Here's a guide with step by step instructions which will help you.
🔗bit.ly/3rbDoyl
(10 / 19)
Here are some popular ones
- VS Code: Feature-rich
- Sublime: Light and simple
- Jupyter: Useful for prototyping
- Pycharm: Full-blown IDE i.e has loads of features.
(11 / 19)
These are online editors which have everything set up for you.
Not to mention colab and kaggle notebooks give you a free GPU for your machine learning workloads.
(12 / 19)
Collab : 🔗colab.research.google.com
Kaggle Notebooks : 🔗kaggle.com/notebooks/welcome
Repl : 🔗repl. it
(13 / 19)
Basics: 🔗youtube.com/watch?v=rfscVS0vtbw
Intermediate: 🔗youtube.com/watch?v=HGOBQPFzWKo
(14 / 19)
Here's a brilliant website which gives you an overview of the windows command prompt, enough for you to get started.
🔗bit.ly/34tmnGd
(15 / 19)
🔗youtube.com/watch?v=oxuRxtrO2Ag
(16 / 19)
It is not important to learn it at the start but I do recommend it.
(17 / 19)
More from Pratham Prasoon
More from Machine learning
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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MAKE PRODUCTS.
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"I lied about my basic beliefs in order to keep a prestigious job. Now that it will be zero-cost to me, I have a few things to say."
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Harvard's discriminatory policies are becoming increasingly well known, across the political spectrum (see, e.g., the recent lawsuit on discrimination against East Asian applications.)
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We know that elite institutions like the one Flier was in (partial) charge of rely on irrelevant status markers like private school education, whiteness, legacy, and ability to charm an old white guy at an interview.
Harvard's discriminatory policies are becoming increasingly well known, across the political spectrum (see, e.g., the recent lawsuit on discrimination against East Asian applications.)
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