DsPy crash course - optimize your LLM pipelines with DsPy (Part 1)

We have well-established frameworks like LangChain and LLlamaIndex for building apps with LLMs. So why another framework like DsPy? How is it different from Langchain and LlamaIndex? Let's answer those questions in this video.

This video is Part 1 which is about the different building blocks of DsPy. Part 2 will be about building an end-to-end pipeline with DsPy. So please stay tuned.

⌚️ ⌚️ ⌚️ TIMESTAMPS ⌚️ ⌚️ ⌚️
0:00 - Intro
1:24 - What is DsPy?
3:12 - PyTorch analogy
5:18 - Building blocks of DsPy
5:31 - Language Models
7:47 - Signatures
9:40 - Modules
12:00 - Data
13:01 - Metrics
14:25 - Optimizers
16:04 - Optimization Algorithms
18:02 - Compiling DsPy Module

RELATED LINKS
DsPy Docs - https://dspy-docs.vercel.app/docs/intro
DsPy GitHub - https://github.com/stanfordnlp/dspy
DsPy paper - https://arxiv.org/abs/2310.03714

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I am a Machine Learning researcher/practitioner who has seen the grind of academia and start-ups. I started my career as a software engineer 15 years ago. Because of my love for Mathematics (coupled with a glimmer of luck), I graduated with a Master's in Computer Vision and Robotics in 2016 when the now happening AI revolution started. Life has changed for the better ever since.

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