🔗 Instill Core is a universal tool for working with unstructured data.

This open-source project offers a comprehensive solution for ETL processing, data preparation for AI, and deployment of LLM models. The platform combines document, image, and video processing into a single workflow, which is especially valuable for RAG scenarios and building AI pipelines.

Instill Core can be easily integrated into existing systems via the Python/TypeScript SDK or CLI. Local execution is possible via Docker, and ready-made recipes allow you to quickly deploy PDF parsing, web scraping, or image segmentation.

🔗 GitHub

🔗 AI Engineer Roadmap

🔗 What is an AI Agent?

An AI agent is a software program that can interact with its environment, gather data, and use that data to achieve predetermined goals. AI agents can choose the best actions to perform to meet those goals.

Key characteristics of AI agents are as follows:

An agent can perform autonomous actions without constant human intervention. Also, they can have a human in the loop to maintain control.

- Agents have a memory to store individual preferences and allow for personalization. It can also store knowledge. An LLM can undertake information processing and decision-making functions.

- Agents must be able to perceive and process the information available from their environment.

- Agents can also use tools such as accessing the internet, using code interpreters and making API calls.

- Agents can also collaborate with other agents or humans.

Multiple types of AI agents are available such as learning agents, simple reflex agents, model-based reflex agents, goal-based agents, and utility-based agents.

A system with AI agents can be built with different architectural approaches.

1 - Single Agent: Agents can serve as personal assistants.
2 - Multi-Agent: Agents can interact with each other in collaborative or competitive ways.
3 - Human Machine: Agents can interact with humans to execute tasks more efficiently.

🔗 Machine learning Project ideas

🔅 Design to Code: Using AI to Build Faster

🌐 Author: Drew Falkman
🔰 Level: Intermediate

⏰ Duration: 1h 21m

🌀 Learn about the artificial intelligence tools that can improve and speed up your design process.

📗 Topics: Artificial Intelligence for Design, Software Development, Artificial Intelligence

📤 Join Artificial intelligence for more courses

📂 Full denoscription

It seems like new artificial intelligence tools are arriving every day, and even if youre interested in using AI in your work, figuring out where to start may seem like an overwhelming undertaking. In this course, Drew Falkman shows designers the ways that AI can help you to build designs faster, make your designs smarter and better, and even improve your dev handoff. Drew surveys the current tools like Figma, Magician, and Sprout, and details their strengths and weaknesses. He also looks at some full-featured design suites that can help you get to prototypes quickly, like Wondershare Mockitt, Visily, and Uizard. He explains how you can use these tools to go from paper sketch or screenshot to wireframe in seconds, or use a prompt to generate an entire prototype. Finally, he shows you how you can use AI to automate the process of turning your designs into code.

📱Artificial intelligence
📱Design to Code: Using AI to Build Faster

🔗 Creating Your AI For Business Roadmap: A Step-by-Step Guide

Identify Business Objectives: Understand how AI can help achieve your goals, whether it's through automation, predictive analytics, AI chatbots, or innovative product development.

Evaluate Data Infrastructure: AI needs quality data. Assess your data collection, storage, and cleanliness to ensure your AI initiatives can thrive.

Assemble a Skilled Team: Combine business insight, technical skills, and data science. Include business strategists, AI specialists, and IT professionals, or seek external expertise as necessary.

Choose Appropriate AI Technology: Select AI tools like ML, NLP, RPA, or Computer Vision, aligned with your business needs.

Prototype Development: Start small with a pilot project to address specific challenges, refining AI models based on performance.

Scale and Optimize: Expand successful prototypes, integrating them into broader business operations and continuously optimizing.

Implement Change Management: Develop strategies to assist your workforce in adapting to AI, including training and understanding AI benefits.

🔗 Life-cycle of Machine Learning Model

🔗 AI Agents

✅ An AI agent roadmap outlines the steps and skills needed to develop and deploy autonomous AI systems.

✅ This includes foundational skills in programming, AI/ML concepts, and data handling, progressing to more advanced topics like NLP, LLMs, and agentic frameworks.

✅ The roadmap also emphasizes practical experience through projects, community engagement, and potentially, internships or open-source contributions.

🔗 How to use Machine Learning to predict fraud

🔅 Introduction to Artificial Intelligence

🌐 Author: Doug Rose
🔰 Level: Beginner

⏰ Duration: 2h 26m

🌀 Get an overview of some of the latest tools and techniques in predictive and generative artificial intelligence (AI).

📗 Topics: Artificial Intelligence

📤 Join Artificial intelligence for more courses

📂 Full denoscription

Computer scientists are just a small slice of people working in artificial intelligence (AI). Most people working with AI are just like you. Theyre professionals, teachers, and students who want to use AI to enhance their products, creativity, and career. AI has been around for over half a century. Despite huge advancements in predictive and generative AI, the core concepts of artificial intelligence are still accessible.This course is designed for project managers, product managers, directors, executives, and students starting a career in AI. First, learn what it means for a system to display “intelligence.” Then, explore the difference between classic predictive AI and newer generative AI. Next, youll get an overview of machine learning algorithms, artificial neural networks, foundation models, and deep learning. From the AI curious to the AI careerist, this course will help you get started with intelligent systems.This course is part of a Professional Certificate from Microsoft.This course is part of a Professional Certificate from Microsoft.

📱Artificial intelligence
📱Introduction to Artificial Intelligence

This repository contains a collection of everything needed to work with libraries related to AI and LLM.

More than 120 libraries, sorted by stages of LLM development:

→ Training, fine-tuning, and evaluation of LLM models
→ Integration and deployment of applications with LLM and RAG
→ Fast and scalable model launching
→ Working with data: extraction, structuring, and synthetic generation
→ Creating autonomous agents based on LLM
→ Prompt optimization and ensuring safe use in production

🔗 Link: https://github.com/Shubhamsaboo/awesome-llm-apps