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I started my career in Data Science back in 2016. Here's a List of Python/ Machine Learning libraries I would urge you to master!! 🚀 A Thread 🧵👇

[Free PDF Download] #Python Machine Learning Projects: assets.digitalocean.com/books/python/m… ———— #BigData #DataScience #AI #MachineLearning #DataScientists #Coding #100DaysOfCode

What is the difference between 𝗦𝘁𝗮𝘁𝗶𝗰 𝗮𝗻𝗱 𝗗𝘆𝗻𝗮𝗺𝗶𝗰 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀? Find out in the Thread 👇 -------- 𝗙𝗼𝗹𝗹𝗼𝘄 𝗺𝗲 and hit 🔔 to 𝗟𝗲𝘃𝗲𝗹 𝗨𝗽 in #MLOps, #MachineLearning, #DataEngineering, #DataScience and overall #Data space!

I continue to try to explain Docker, in a sketchnote way, in a visual way. Let's focus on Content trust: dev.to/aurelievache/u… Why and how? Hope you'll like this new sketchnote about Docker. DEV Community The Docker Dev DockerTrends

If you're looking to dive deeper into #ChatGPT and other generative #AI tech, the OpenAI cookbook is an awesome resource! 🔥 It's currently the top trending repo on @GitHub, so you know it's worth checking out! ;) 🐙→ github.com/openai/openai-…

9 steps in learning Machine Learning 1) Basic programming 2) Linear Algebra 3) Multivariate Calculus 4) Probability and Statistics 5) Algos 6) Version control 7) Basic ML (regression, classification, clustering) 8) Python for ML libraries 9) Deep Learning

An introduction to Probabilities and Statistics. Check out "Seeing Theory" from Brown University: seeing-theory.brown.edu This interactive website will take you through the concepts you need in machine learning for FREE.

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What do you need to know about distributed joins in Spark? 🧵 #DataEngineering #Data #MLOps #MachineLearning

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ChatGPT is Old and Unimpressive Now. 90% didn't know there are AI Tools built Especially for: → Researchers → Teachers → Students Here're 6 Free AI Tools, that will change the game.

Meet Media Agent, my new project 🚀 Built with LangChain, 🔌 it connects to @Twitter and Reddit, Inc. 🔎 extracts posts based on search queries or usernames 💡 summarizes and embeds them in a vector db 💬 chats with them from the terminal Harrison Chase github.com/ahmedbesbes/me…

Learn about Generative AI from scratch with these 9 introductory courses released by Google: Link: cloudskillsboost.google/journeys/118

Everyone should learn how to fine-tune LLMs. However, LLMs barely fit in GPU memory❗️ This is where fine-tuning & more importantly parameter efficient fine-tuning (PEFT) become essential. Let's understand them today:

My deep learning course UNIGE_en is available on-line. 1000+ slides, ~20h of screen-casts. Full of examples in PyTorch. fleuret.org/dlc/ And my "Little Book of Deep Learning" is available as a phone-formatted pdf (400k downloads!) fleuret.org/lbdl/

Biggest regret is Jio subscription @JioCinema #JioCinema👎🏻

Mathematics for Machine Learning from University of Berkeley. Learn: • Linear Algebra • Calculus and Optimization • Probabilities 100% Free. Download it here: gwthomas.github.io/docs/math4ml.p…

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