Build a Web Scrapping AI Agent with RAG in just 30 lines of Python Code (step-by-step instructions): We'll use ScrapeGraphAI, a Python library that uses LLMs to create smart scraping pipelines.

It involves four main steps:
1. Fetch: Retrieve the data
2. Parse: Analyze and structure the data
3. RAG: Processes the parsed data to find relevant information
4. Generate Answer

Document OCR in 90+ languages using python (100% free and without internet): For document OCR, we'll use opensource toolkit Surya.

Python toolkit that does:
• OCR in 90+ languages
• Line-level text detection in any language
• Layout analysis (table, image detection)
• Reading order detection
• Outperforms Tesseract, on par with Google Cloud vision

Build a LLM app with RAG to chat with any AI newsletter on Substack in just 30 lines of Python Code (step-by-step instructions): 1. Import necessary libraries

• Streamlit for building the web app
• Embedchain for the RAG functionality
• tempfile for creating temporary files and directories

Build a RAG app with Llama-3 running locally on your computer
(100% free and without internet): 1. Install the necessary Python Libraries

Run the following command from your terminal.

Build a LLM app with RAG to chat with your Gmail Inbox in just 30 lines of Python Code (step-by-step instructions): 1. Install the necessary Python Libraries

Run the following command from your terminal.

Build a LLM app with RAG to chat with YouTube videos in just 30 lines of Python Code (step-by-step instructions): 1. Import necessary libraries

• Streamlit for building the web app
• Embedchain for the RAG functionality
• tempfile for creating temporary files and directories

Build a LLM app with RAG to chat with PDF in just 30 lines of Python Code
(step-by-step instructions): 1. Import necessary libraries

• Streamlit for building the web app
• Embedchain for the RAG functionality
• tempfile for creating temporary files and directories

Build LLM app with RAG in a few lines of Python Code (step-by-step instructions): 1. Install Embedchain

Embedchain is an opensource AI framework for creating LLM apps with RAG. It effectively segments data into manageable chunks, generates relevant embeddings, and stores them in a vector database for optimized retrieval.

3 ways to run Llama-3 locally (100% free and without internet): 1. GPT4All

An open-source project that provides tools and software to run powerful LLMs on your computer, without needing access to expensive GPU hardware or cloud services.

30-day study plan to learn AI and Machine Learning

Bookmark for reference 📌 Day 1: Introduction to AI and ML

• Objective: Understand AI, ML, and Deep Learning (DL)
• Task: Read the introductory chapter of “Artificial Intelligence: A Guide for Thinking Humans” by Melanie Mitchell.
• Exercise: Summarize the differences between AI, ML, and DL.

Stop LLM hallucination with this Python library

Outlines is a Python library that makes text generated by large language models (LLMs) more consistent and predictable.

It lets you control how LLMs generate text, making sure they follow a specific, expected format. In this post, you'll read about:

1. Make LLMs answer MCQs without Hallucination
2. Make LLMs generate efficient JSON
3. Prompt Management with Templates

Before you move forward, subscribe to Unwind AI for more such AI updates: unwindai.substack.com

Support Vector Machines (SVM) Clearly Explained with Python Code: What is SVM?

SVM is a supervised ML algorithm primarily used for classification tasks.

Imagine you're at a party, and you want to separate the pizza lovers from the burger lovers. SVM is the friend who draws the perfect line to divide them neatly.

Drag & Drop to build AI agents 🤯

Meet n8n, a visual UI for building AI agents with LangChain without writing a single line of Python code.

Want to build automation around LLM apps with Nocode, get started now:

How does it work?

1. Connect & Set Up: Choose your n8n experience and set triggers to fetch data across apps.

2. Integrate Using App Nodes: Utilize 400+ app nodes to manage your data.

3. Automate: Let your workflow handle tasks, from monthly sync to massive data executions.

ChatGPT just went FULLY multimodal 🤯

With one update, OpenAI killed 1000s of AI startups. ChatGPT’s strategy: Consolidate, Innovate, & Dominate.

ChatGPT becomes the ultimate AI super-app combining Midjourney, PDF Chat, Perplexity AI, and advanced Data analysis all in one app. Here’s is what you can do with multimodal ChatGPT (Example by @ldjconfirmed)

Generate Image, Edit images with text, chat with images, documents and so much more 🤯

Drag & Drop to build AI agents 🤯

Introducing n8n, a visual UI for building AI agents with LangChain without writing a single line of Python code.

Now build automation around LLM apps with NoCode and give superpowers to ChatGPT. How does it work?

1. Connect & Set Up: Choose your n8n experience and set triggers to fetch data across apps.

2. Integrate Using App Nodes: Utilize 400+ app nodes to manage your data.

3. Automate: Let your workflow handle tasks, from monthly sync to massive data executions.

LLMOps is the holy grail for deploying LLMs in Production.

Here is the roadmap to go from playground to production: Platforms for LLMs

Think of LLM platforms as your personal Formula 1 pit crew - managing the heavy-lifting of infrastructure, fine-tuning, versioning, and deployment. They come in two flavors:

1. NoCode/LowCode platforms
2. Customizable Code-first platforms.

Don't pay ridiculous amounts of money to study Python, Data Science, and Machine Learning.

Learn from the experts at Google, IBM, Stanford, MIT, and Harvard universities for FREE.

(A thread) 👇 📌 twitter.com/i/web/status/1… 1. Introduction to Computer Science and Programming in Python

YouTube playlist for beginners with little or no programming experience.

👉 youtube.com/playlist?list=…

ChatGPT Code Interpreter just launched 24 hrs ago

It has already taken the internet by storm and blowing everyone's mind!

Here are 15 amazing things that it can do: https://t.co/9toL4OWCxstwitter.com/i/web/status/1…
Bookmark this thread to come to back to when you experiment with Code Interpreter.

In this thread, you will see how Code Interpreter can:
- Be a data scientist
- Extract text from images (OCR)
- Generate animations and Videos
- Generate QR codes
- & so much more!

Are you ready to take your machine learning and data science skills to the next level?

I've got an incredible resource to share with you!

(A thread) 👇🧵 I came across @brilliantorg courses that teach you from first principles, making complex concepts intuitive and engaging.

Turn problems into simple exercises!

Top 10 ChatGPT Alternatives!

No signup required.

Bookmark this 📌 1. Perplexity AI

Perplexity AI unlocks the power of knowledge with information discovery and sharing. It can access the latest information using the web browsing feature.

perplexity.ai

Tired of dull QR codes? 😴

Now you can transform your QR codes using AI!

Stable Diffusion with Control Net = Awesome QR codes 🔥

(A thread) 🧵👇 1. Anime QR Code