This tutorial walks you through building a -- that transforms CSV data into insightful visualizations based on natural language queries.
You’ll learn how to leverage OpenAI’s structured outputs with Pydantic for consistent results, use the OpenAI Files API for seamless data uploads, employ Pandas for robust data analysis, and create stunning charts with Plotly.
Using the (, ), we’ll build an agent that answers questions like “ ?” by profiling data, recommending charts, and generating visualizations.
My new article, "Automating AI Deployment with Coolify & GitHub (Free),” dives into DevOps for AI projects. Inspired by The Phoenix Project, it breaks down CI/CD pipelines, traces DevOps tool evolution, and guides you through setting up Coolify for free, self-hosted deployments. Perfect for AI devs and business owners, from beginners to pros. Simplify your workflow and save costs!
I wrote a beginner-friendly guide to help anyone dive into AI using Hugging Face, the "GitHub for AI." It breaks down the machine learning pipeline with a simple analogy, explores Hugging Face’s features (models, datasets, tokenizers, Spaces), and includes hands-on tutorials to write your first AI script—no prior experience needed! You’ll learn to analyze sentiment, explore datasets, train models, and deploy apps. Perfect for curious learners or hobbyists wanting to experiment with AI. Would love to hear your thoughts or what you’re building with AI!
I wrote a beginner-friendly guide on using OpenAI’s Function Calling to parse resumes into structured JSON—name, skills, experience, ready for your DB. Includes Python code, a GitHub repo, and a YouTube walkthrough.
Anyone automating unstructured data with AI? Thoughts on scaling this for bigger datasets?
Generative AI is transforming business—unlocking ways to delight customers, empower employees, and streamline operations. But here’s the catch: it’s a tool that demands wisdom. Used well, it drives efficiency, revenue, and quality while cutting risks and costs. Used poorly, it can backfire spectacularly.
As an AI engineering consultant, I’ve seen both sides. This guide cuts through the noise, outlining the right and wrong ways to integrate AI into your operations, ensuring it drives efficiencies, generates revenue, improves quality, mitigates risks, and reduces costs without costly missteps.
If your resume isn't getting the attention it deserves, it's time for an upgrade. Knitroots' CV Booster ensures your portfolio is personalized, well-structured, and optimized for ATS systems. Trusted by 100+ users, it’s designed to elevate your tech career.
- Tailored resume insights
- Grammar-perfect formatting
- Automation to speed up your CV review
You’ll learn how to leverage OpenAI’s structured outputs with Pydantic for consistent results, use the OpenAI Files API for seamless data uploads, employ Pandas for robust data analysis, and create stunning charts with Plotly.
Using the (, ), we’ll build an agent that answers questions like “ ?” by profiling data, recommending charts, and generating visualizations.