𝗜 𝘀𝘁𝗮𝗿𝘁𝗲𝗱 𝗺𝘆 𝗰𝗮𝗿𝗲𝗲𝗿 𝗶𝗻 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗯𝗮𝗰𝗸 𝗶𝗻 𝟮𝟬𝟭𝟲 ⏳

𝗛𝗲𝗿𝗲'𝘀 𝗮 𝗹𝗶𝘀𝘁 𝗼𝗳 𝗣𝘆𝘁𝗵𝗼𝗻 𝗹𝗶𝗯𝗿𝗮𝗿𝗶𝗲𝘀 𝗳𝗼𝗿 𝗠𝗟 𝘁𝗵𝗮𝘁 𝗜 𝗵𝗶𝗴𝗵𝗹𝘆 𝗿𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱 𝗺𝗮𝘀𝘁𝗲𝗿𝗶𝗻𝗴!

Find links to official docs & some good tutorials...👇

1️⃣ 𝗡𝘂𝗺𝗣𝘆

The most popular Python library for scientific computing.

Docs: 👇
https://lnkd.in/d2nHnVpY

Video Tutorial: 👇
https://lnkd.in/dCuEFrrC

2️⃣ 𝗣𝗮𝗻𝗱𝗮𝘀

Go to Python library for data manipulation and analysis.

Docs: 👇
https://lnkd.in/dY38iRdf

Video Tutorial: 👇
https://lnkd.in/dnGYVw82

3️⃣ 𝗦𝗰𝗶𝗸𝗶𝘁-𝗟𝗲𝗮𝗿𝗻

Provides tools and algorithms for working with data and a wide range of ML tasks.

Docs:👇
https://lnkd.in/dX3AD_CB

Video Tutorial: 👇
https://lnkd.in/dnm-mwMM

4️⃣ 𝗣𝘆𝗧𝗼𝗿𝗰𝗵

The most loved Deep Learning frame work.

A must have tool in your Arsenal!!

Docs: 👇
https://lnkd.in/d48ivSY7

Video Tutorial:👇
https://lnkd.in/dug4cdGz

5️⃣ 𝗧𝗲𝗻𝘀𝗼𝗿𝗙𝗹𝗼𝘄

The most popular Deep Learning frame work!

Yo can master one of PyTorch or TensorFlow but must have a read-write capability for both. ✅

Tf docs are the best place to learn.

Docs: 👇
https://lnkd.in/dhpQjYAc

6️⃣ 𝗠𝗮𝘁𝗽𝗹𝗼𝘁𝗹𝗶𝗯

The best tool for Data Visualisation!! 📊

Docs: 👇 https://lnkd.in/ddgmGeh2

Video Tutorial: 👇
https://lnkd.in/dAvkzUvd
7️⃣ 𝗢𝗽𝗲𝗻𝗖𝗩

Working in computer vision❓

You must master this library to stand out!!

Docs: 👇
https://lnkd.in/d6vYBus5

8️⃣ 𝗛𝘂𝗴𝗴𝗶𝗻𝗴𝗙𝗮𝗰𝗲 🤗

97,436 Models 🔥
15,690 Datasets 🔥

Everything open-sourced 🙌

If not already using go & start using HF 🤗

Docs: 👇
huggingface.co/docs

9️⃣ 𝗝𝗔𝗫

Not just another PyTorch/TensorFlow❗️

A library that offers unique capabilities for high-performance machine learning.

I've recently started learning this & loving it as I progress!!

Docs: 👇
https://lnkd.in/dRgRBqCN

Video Tutorial: 👇
https://lnkd.in/dT_jkxMU

🔟 𝗟𝗮𝗻𝗴𝗖𝗵𝗮𝗶𝗻

Your go to framework when working with LLMs.

Docs: 👇
https://lnkd.in/drG--U3r

Free course: 👇
https://lnkd.in/dyGcqPqq

1️⃣1️⃣ 𝗣𝘆𝗧𝗼𝗿𝗰𝗵 𝗟𝗶𝗴𝗵𝘁𝗻𝗶𝗻𝗴 ⚡️

Created by Lightning AI, a structured & scalable PyTorch wrapper for streamlined training!

Offers automatic optimization, multi-GPU support, & advanced logging.