Generative AI has exploded, with enterprises trying to figure out how to use Large Language Models to solve use cases. Many AI developers, experts and companies are sharing open source solutions. They post tutorials which are easy to follow and lead us into thinking of possible use cases. As new tutorials come out, I will keep trying them out myself and sharing here, so we can all learn together and benefit.
Andrew Ng's tutorials on DeepLearning.ai have helped me with understanding of Large Language Models and implementing them in real world examples. My most favorite course taught ny Andrew Ng and Harrison Chase is LangChain for LLM Application Development. At the end of this course you will learn to "apply LLMs to your proprietary data to build personal assistants and specialized chatbots" This solution has the most applications and is a powerful one. I have used this for multiple use cases.
The courses listed below will help you learn real-world applicability of large language models. Dive in and start building prototypes. That's the best way to learn.
For quick prototyping, use Streamlit: https://www.youtube.com/@streamlitofficial
In this On-Demand episode, Cassie teams up with Swati Gharse to delve into the Llama 2 model and its utilization on Azure.: https://youtu.be/zFTnc8vbfVI
Deeplearning.ai just released "Large Language Models with Semantic Search”, built with Cohere, and taught by Jay Alammar and Luis Serrano.
https://www.deeplearning.ai/short-courses/large-language-models-semantic-search/
Courses by Google Cloud https://www.cloudskillsboost.google/journeys/118
Tutorial by Abhishekh Thakur of Hugging Face https://youtu.be/3fsn19OI_C8
Learn from Abhishekh Thakur of Hugging Face: https://youtu.be/PE0DQlQItro
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