---
title: 'Top AI Frameworks to Learn in 2026 | Best AI Frameworks Explained'
source: 'https://youtube.com/watch?v=MNSS8fGVD8I'
video_id: 'MNSS8fGVD8I'
date: 2026-08-08
duration_sec: 95
---

# Top AI Frameworks to Learn in 2026 | Best AI Frameworks Explained

> Source: [Top AI Frameworks to Learn in 2026 | Best AI Frameworks Explained](https://youtube.com/watch?v=MNSS8fGVD8I)

## Summary

This video provides a concise overview of the most important AI frameworks to learn in 2026, covering essential tools for machine learning, deep learning, and AI agent development. It outlines seven key frameworks, from scikit-learn for beginners to advanced tools like LangGraph and CrewAI for building AI agents, and emphasizes a structured learning path.

### Key Points

- **Scikit-learn for ML Basics** [00:02] — Scikit-learn is essential for understanding the basics of machine classification and model training.
- **PyTorch for Deep Learning** [00:16] — PyTorch is a crucial deep learning framework, especially for working with neural networks and AI models.
- **TensorFlow and Keras** [00:28] — Keras is the high-level API of TensorFlow, offering a beginner-friendly way to build deep learning models.
- **Hugging Face Transformers** [00:41] — This framework is vital for working with LLMs and multimodal AI models, including text, vision, audio, and video.
- **LangChain and LangGraph** [00:41] — LangChain helps build AI applications, while LangGraph is for creating reliable AI agents with memory, tool use, and multi-step workflows.
- **LlamaIndex for RAG** [00:57] — LlamaIndex is essential for building RAG apps that connect AI with PDFs, APIs, SQL, and business data.
- **CrewAI and Agent SDKs** [01:14] — Explore CrewAI, semantic kernel, or OpenAI agent SDK for building AI agents, but don't try to learn everything at once.

### Conclusion

The video recommends a structured learning path: start with machine learning basics, then deep learning, then LLMs, and finally Agentic AI. It encourages viewers to focus on one framework at a time and engage with the community.

## Transcript

2026, then [music] these are the frameworks you should know. First is scikit-learn. This is where you're going to understand the basics of machine classification, and model training. Second one is learn PyTorch. PyTorch is
one of the most important [music] deep learning frameworks, especially if you want to work with neural networks and AI models. [music] Third is learn TensorFlow and Keras. Keras is the high-level API of TensorFlow, [music]
and it is useful when you want beginner-friendly way to build deep learning model. Fourth is Hugging Face Transformers. [music] And this is very important for working with LLMs, text, visions, audio, video, [music] and
multimodal AI models. Fifth is LangChain and LangGraph. LangChain helps you build AI applications, while LangGraph is useful for building reliable AI agents with memory, tool use, and multi-step workflows. Sixth is learn LlamaIndex. If
you want to build RAG apps that connect AI with PDF, APIs, SQL, and business data, then LlamaIndex is a must-know framework. And finally, explore CrewAI, which is a semantic kernel or OpenAI agent SDK if you want to build AI agent
don't try to learn everything at the first go. Start with machine learning basics, then go into deep learning, then learn about LLMs, and then explore Agentic AI. So, guys, these are the smartest AI
framework for 2026. Let us know in the comment section below Let us know in the comment section below which one are you learning right now.