Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

I'm excited to introduce my FREE AI Pandas Data Analyst Copilot which created a data analysis report with dozens of charts from my questions in under 30 seconds. Today, I'll share with you how to automate data analysis with my Pandas AI Agent + Copilot, which is available on...

mdancho84's profile picture

Matt Dancho (Business Science)

100,462 subscribers

12,736 Aufrufe • vor 1 Jahr •via X (Twitter)

Gesundheit & WellnessWissenschaft & TechnologieBildung
LIVE

Anya Rossi• Live Now

Private livecam show

8 Kommentare

Profilbild von 🔥 Matt Dancho (Business Science) 🔥
🔥 Matt Dancho (Business Science) 🔥vor 1 Jahr

P.S. Want live AI + Data Science training with me for free? Register for my next live AI for Data Scientists Workshop here:

Profilbild von Breadcrumb
Breadcrumbvor 1 Jahr

Looking to automate reporting? Use AI agents to turn spreadsheets to reports in minutes without any coding.

Profilbild von Vishwaraj Singh
Vishwaraj Singhvor 1 Jahr

Excited Great stuff

Profilbild von David Ellis
David Ellisvor 1 Jahr

This tool revolutionizes how efficiently we handle data analysis tasks.

Profilbild von Machine Bee
Machine Beevor 1 Jahr

Access to efficient data analysis tools can streamline decision-making processes significantly. Will consider testing its utility for complex datasets.

Profilbild von Dante Data
Dante Datavor 1 Jahr

The potential for increased productivity through AI-driven analysis is noteworthy.

Profilbild von Don Quantum
Don Quantumvor 1 Jahr

Automating data analysis is invaluable. Excited to explore GitHub for this tool.

Profilbild von Node Whisperer
Node Whisperervor 1 Jahr

Having access to an AI Pandas Copilot could transform data analysis approach significantly.

Ähnliche Videos

I'm excited to introduce my AI Machine Learning Agent that built 32 ML models in 30 seconds. Today, I'll share with you how to automate building 100s of ML models with the AI ML Agent, which is available on GitHub. We'll create an ML Agent focusing on a Customer Churn Problem. I'll guide you through setting up the ML Agent, creating dozens of ML models, and loading the best model for production. This AI is a huge time-saver! Table of Contents: 00:00 Introduction to my AI Data Science Team 02:56 Setting Up AI Data Science Team 04:48 Running the ML Agent Code 07:12 Create (and Run) the AI Machine Learning Agent 09:53 Reviewing ML Model Summary 12:00 Saving and Loading Models 13:00 Next Steps + Project Roadmap + AI Bootcamp Github to AI Data Science Team (Data Science Agents): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter: P.S. - Want to learn how to build AI projects companies actually want? (live Python Code) On Wednesday, May 21st, I'm sharing one of my best AI Projects: AI Customer Segmentation Agent with Python Register here (570+ registered):
15:38

I'm excited to introduce my AI Machine Learning Agent that built 32 ML models in 30 seconds. Today, I'll share with you how to automate building 100s of ML models with the AI ML Agent, which is available on GitHub. We'll create an ML Agent focusing on a Customer Churn Problem. I'll guide you through setting up the ML Agent, creating dozens of ML models, and loading the best model for production. This AI is a huge time-saver! Table of Contents: 00:00 Introduction to my AI Data Science Team 02:56 Setting Up AI Data Science Team 04:48 Running the ML Agent Code 07:12 Create (and Run) the AI Machine Learning Agent 09:53 Reviewing ML Model Summary 12:00 Saving and Loading Models 13:00 Next Steps + Project Roadmap + AI Bootcamp Github to AI Data Science Team (Data Science Agents): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter: P.S. - Want to learn how to build AI projects companies actually want? (live Python Code) On Wednesday, May 21st, I'm sharing one of my best AI Projects: AI Customer Segmentation Agent with Python Register here (570+ registered):

Matt Dancho (Business Science)

35,452 Aufrufe • vor 1 Jahr

I'm excited to introduce my AI Machine Learning Agent that built 32 ML models in 30 seconds. Today, I'll share with you how to automate building 100s of ML models with the AI ML Agent, which is available on GitHub. We'll create an ML Agent focusing on a Customer Churn Problem. I'll guide you through setting up the ML Agent, creating dozens of ML models, and loading the best model for production. This AI is a huge time-saver! Table of Contents: 00:00 Introduction to my AI Data Science Team 02:56 Setting Up AI Data Science Team 04:48 Running the ML Agent Code 07:12 Create (and Run) the AI Machine Learning Agent 09:53 Reviewing ML Model Summary 12:00 Saving and Loading Models 13:00 Next Steps + Project Roadmap + AI Bootcamp Github to AI Data Science Team (Army of Copilots): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter: P.S. - Want to learn how to build AI projects companies actually want? (live Python Code) On Wednesday, January 29th, I'm sharing one of my best AI Projects: Time Series Forecasting with AI Register here (1570+ registered):
15:38

I'm excited to introduce my AI Machine Learning Agent that built 32 ML models in 30 seconds. Today, I'll share with you how to automate building 100s of ML models with the AI ML Agent, which is available on GitHub. We'll create an ML Agent focusing on a Customer Churn Problem. I'll guide you through setting up the ML Agent, creating dozens of ML models, and loading the best model for production. This AI is a huge time-saver! Table of Contents: 00:00 Introduction to my AI Data Science Team 02:56 Setting Up AI Data Science Team 04:48 Running the ML Agent Code 07:12 Create (and Run) the AI Machine Learning Agent 09:53 Reviewing ML Model Summary 12:00 Saving and Loading Models 13:00 Next Steps + Project Roadmap + AI Bootcamp Github to AI Data Science Team (Army of Copilots): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter: P.S. - Want to learn how to build AI projects companies actually want? (live Python Code) On Wednesday, January 29th, I'm sharing one of my best AI Projects: Time Series Forecasting with AI Register here (1570+ registered):

Matt Dancho (Business Science)

242,084 Aufrufe • vor 1 Jahr

I'm excited to introduce my AI Exploratory Data Analysis (EDA) Agent that built EDA reports, performs correlation analysis, and missing data analysis in 20 seconds. Today, I'll share with you how to automate creating EDA reports with the AI EDA Agent, which is available on GitHub. We'll create an EDA Agent focusing on a Customer Churn Problem. I'll guide you through setting up the EDA Agent, creating EDA reports, and analyzing the findings. This AI agent is a huge time-saver! Table of Contents: 00:00 Introduction to EDA Tools Agent 01:20 Get the AI Data Science Team 04:49 Create the EDA Tools Agent 06:35 Using the EDA Tools Agent for Missing Data and Correlation Funnels 10:00 Get SweetViz EDA Reports with AI 12:00 8-Week AI Bootcamp Github to AI Data Science Team (Army of Copilots): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter: P.S. - Want to learn how to build AI projects companies actually want? (live Python Code) On Wednesday, February 12th, I'm sharing one of my best AI Projects: Business Intelligence with AI Register here (1570+ registered):
13:04

I'm excited to introduce my AI Exploratory Data Analysis (EDA) Agent that built EDA reports, performs correlation analysis, and missing data analysis in 20 seconds. Today, I'll share with you how to automate creating EDA reports with the AI EDA Agent, which is available on GitHub. We'll create an EDA Agent focusing on a Customer Churn Problem. I'll guide you through setting up the EDA Agent, creating EDA reports, and analyzing the findings. This AI agent is a huge time-saver! Table of Contents: 00:00 Introduction to EDA Tools Agent 01:20 Get the AI Data Science Team 04:49 Create the EDA Tools Agent 06:35 Using the EDA Tools Agent for Missing Data and Correlation Funnels 10:00 Get SweetViz EDA Reports with AI 12:00 8-Week AI Bootcamp Github to AI Data Science Team (Army of Copilots): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter: P.S. - Want to learn how to build AI projects companies actually want? (live Python Code) On Wednesday, February 12th, I'm sharing one of my best AI Projects: Business Intelligence with AI Register here (1570+ registered):

Matt Dancho (Business Science)

31,079 Aufrufe • vor 1 Jahr

Introducing my SQL Agent: How to automate SQL with AI. Today I'll share how to make a SQL AI Agent that can automatically connect to databases, understand the tables and schema, and write and execute high-quality SQL queries. I'll guide you through setting up the SQL Agent, creating dozens of SQL queries, and returning the data from those queries. This AI is a huge help!! Table of Contents: 00:00 Introduction 01:30 How to Get The AI Data Science Agents 03:23 AI Tips Newsletter: Get The Code 04:00 Project Setup 06:30 Setting Up Your First SQL Agent 11:00 Running SQL Queries with the SQL Agent 14:25 Next Steps, Project Roadmap, & AI Bootcamp Github to AI Data Science Team (Army of Copilots): Get the Code by Joining my Python AI/ML Tips Newsletter: P.S. - Want to learn how to build AI projects companies actually want? (live Python Code) On Wednesday, February 12th, I'm sharing one of my best AI Projects: SQL-Writing Business Intelligence Team Register here (570+ registered):
17:04

Introducing my SQL Agent: How to automate SQL with AI. Today I'll share how to make a SQL AI Agent that can automatically connect to databases, understand the tables and schema, and write and execute high-quality SQL queries. I'll guide you through setting up the SQL Agent, creating dozens of SQL queries, and returning the data from those queries. This AI is a huge help!! Table of Contents: 00:00 Introduction 01:30 How to Get The AI Data Science Agents 03:23 AI Tips Newsletter: Get The Code 04:00 Project Setup 06:30 Setting Up Your First SQL Agent 11:00 Running SQL Queries with the SQL Agent 14:25 Next Steps, Project Roadmap, & AI Bootcamp Github to AI Data Science Team (Army of Copilots): Get the Code by Joining my Python AI/ML Tips Newsletter: P.S. - Want to learn how to build AI projects companies actually want? (live Python Code) On Wednesday, February 12th, I'm sharing one of my best AI Projects: SQL-Writing Business Intelligence Team Register here (570+ registered):

Matt Dancho (Business Science)

77,293 Aufrufe • vor 1 Jahr

How to automate data cleaning with AI. Today, I'll show you how to automate data cleaning using my free AI co-pilot available on GitHub. We'll create an AI co-pilot to automate data-cleaning tasks, focusing on cleaning a customer churn dataset. I'll guide you through setting up the co-pilot and using it effectively. This AI agent is a big help. Table of Contents: 00:00 Introduction 02:52 Setting Up Libraries 06:31 Setting Up LLMs 08:31 Creating Data Cleaner Code 11:02 Data Cleaning Process 13:02 Examining Data Cleaner Function 15:02 Final Thoughts Github to AI Data Science Team (Army of Copilots): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter:
16:44

How to automate data cleaning with AI. Today, I'll show you how to automate data cleaning using my free AI co-pilot available on GitHub. We'll create an AI co-pilot to automate data-cleaning tasks, focusing on cleaning a customer churn dataset. I'll guide you through setting up the co-pilot and using it effectively. This AI agent is a big help. Table of Contents: 00:00 Introduction 02:52 Setting Up Libraries 06:31 Setting Up LLMs 08:31 Creating Data Cleaner Code 11:02 Data Cleaning Process 13:02 Examining Data Cleaner Function 15:02 Final Thoughts Github to AI Data Science Team (Army of Copilots): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter:

Matt Dancho (Business Science)

50,794 Aufrufe • vor 1 Jahr

I made an AI data science team with Python. I'm excited to share my new project, the AI Data Science Team, a Python package for creating AI co-pilots and agents to assist in common data science tasks. I walk you through the GitHub page, showcasing the progress and potential of this project. I'll explain how these agents can streamline tasks like code generation and modeling pipeline creation, making data science projects more efficient. Introduction to AI Data Science Team Project Integrating Human-in-the-Loop Example: Accessing Agents for Feature Engineering Setting up Feature Engineering Agent Code On GitHub: Python AI-Tips Newsletter (stay updated as I build this project in the open):
12:57

I made an AI data science team with Python. I'm excited to share my new project, the AI Data Science Team, a Python package for creating AI co-pilots and agents to assist in common data science tasks. I walk you through the GitHub page, showcasing the progress and potential of this project. I'll explain how these agents can streamline tasks like code generation and modeling pipeline creation, making data science projects more efficient. Introduction to AI Data Science Team Project Integrating Human-in-the-Loop Example: Accessing Agents for Feature Engineering Setting up Feature Engineering Agent Code On GitHub: Python AI-Tips Newsletter (stay updated as I build this project in the open):

Matt Dancho (Business Science)

11,799 Aufrufe • vor 1 Jahr

Microsoft 365 Copilot in Excel with Python, now in preview, allows you to: ➡️ Perform advanced data analysis ➡️ Create sophisticated visualizations Unlock the power of Python with Copilot. #AI #Excel
0:33

Microsoft 365 Copilot in Excel with Python, now in preview, allows you to: ➡️ Perform advanced data analysis ➡️ Create sophisticated visualizations Unlock the power of Python with Copilot. #AI #Excel

Microsoft 365

100,591 Aufrufe • vor 1 Jahr

This guy built an entire AI data science team in Python. Then open-sourced (100% free). It automates data science workflows with AI, including data loading, cleaning, exploratory analysis, and feature engineering. And it tracks each step in a 100% reproducible pipeline. 00:00 Project Overview 01:32 Diving into the AI Data Science Workflow and Data Loading 02:10 Data Wrangling and Cleaning 03:33 Data Visualization Insights & Plotting 04:08 Feature Engineering 05:00 Live 1-Hour Workshop 05:44 AI Data Science Team Python Library 🔗 AI Data Science Team On GitHub (Give it a Star) 🔗 Join My Next Live 1-Hour Agentic AI Workshop (Free):
7:04

This guy built an entire AI data science team in Python. Then open-sourced (100% free). It automates data science workflows with AI, including data loading, cleaning, exploratory analysis, and feature engineering. And it tracks each step in a 100% reproducible pipeline. 00:00 Project Overview 01:32 Diving into the AI Data Science Workflow and Data Loading 02:10 Data Wrangling and Cleaning 03:33 Data Visualization Insights & Plotting 04:08 Feature Engineering 05:00 Live 1-Hour Workshop 05:44 AI Data Science Team Python Library 🔗 AI Data Science Team On GitHub (Give it a Star) 🔗 Join My Next Live 1-Hour Agentic AI Workshop (Free):

Matt Dancho (Business Science)

85,386 Aufrufe • vor 8 Monaten

THIS IS ONE OF MY BEST FEATURES ON THE PUNTRR APP IT HELP YOU MAKE RISKY GAMES SAFER DOWNLOAD PUNTRR AI APP TO HELP YOU WITH 80%-90% SURE PREDICTIONS USING AI DATA USE MY CODE: KOMBO to access be able to use the APP for free for 7days APPLE ANDROID
2:12

THIS IS ONE OF MY BEST FEATURES ON THE PUNTRR APP IT HELP YOU MAKE RISKY GAMES SAFER DOWNLOAD PUNTRR AI APP TO HELP YOU WITH 80%-90% SURE PREDICTIONS USING AI DATA USE MY CODE: KOMBO to access be able to use the APP for free for 7days APPLE ANDROID

KOMBO™

141,169 Aufrufe • vor 5 Monaten

Data Models - Better AI Code in 5 Minutes Your AI isn't consistent because you're missing one file. I had the same problem until I started using a data model file. In this video, I'm showing you the exact two prompts I use: one generates the data model, the second uses it to generate features without breaking my app. Testing this with AnimeLeak (my actual production app) adding an admin approval feature. Using Droid with Sonnet 4.5 in spec mode, but this works in Cursor, Claude, or whatever you're using. KEY TIMESTAMPS 00:00 - The One File Your AI is Missing 00:44 - Prompt 1: Generate a Data Model 01:12 - The Result: Data Model Documentation 02:12 - Prompt 2: Implement a New Feature 03:00 - Reviewing the AI-Generated Spec 04:17 - Why This Workflow is So Powerful 04:32 - Your 3-Step Action Plan 05:12 - Next Video: Live Code Generation
5:30

Data Models - Better AI Code in 5 Minutes Your AI isn't consistent because you're missing one file. I had the same problem until I started using a data model file. In this video, I'm showing you the exact two prompts I use: one generates the data model, the second uses it to generate features without breaking my app. Testing this with AnimeLeak (my actual production app) adding an admin approval feature. Using Droid with Sonnet 4.5 in spec mode, but this works in Cursor, Claude, or whatever you're using. KEY TIMESTAMPS 00:00 - The One File Your AI is Missing 00:44 - Prompt 1: Generate a Data Model 01:12 - The Result: Data Model Documentation 02:12 - Prompt 2: Implement a New Feature 03:00 - Reviewing the AI-Generated Spec 04:17 - Why This Workflow is So Powerful 04:32 - Your 3-Step Action Plan 05:12 - Next Video: Live Code Generation

Ray Fernando

15,479 Aufrufe • vor 10 Monaten

Now that my college basketball career is over, I'm excited to share with you what I'll be doing next... Partnering with Formula Bot - the AI-powered data analyst that helps you work faster & smarter with data. It can convert your text to data analysis, visualizations & more.
0:20

Now that my college basketball career is over, I'm excited to share with you what I'll be doing next... Partnering with Formula Bot - the AI-powered data analyst that helps you work faster & smarter with data. It can convert your text to data analysis, visualizations & more.

Jack Gohlke

2,817,983 Aufrufe • vor 2 Jahren

"Claude Code is the first AI tool that can actually recreate how a data scientist thinks." Here's my new episode with Sumeet Marwaha (Head of Data at Brex) on exactly how to build an AI analyst with Claude Code. We covered: ✅ 3 queries to build a data analyst MCP ✅ How to give the analyst both data + context ✅ Exclusive Brex data on which AI tools are crushing it in startups and enterprise Some quotes from Sumeet: "I've set up dashboards many times in my career. They end up getting ignored. Claude will always read it. Claude will always ask the right questions." "You have to set up Claude Code to not just look at the data. It should be able to search Slack, find the incident, and understand why your metrics look wrong." "This tool is absolutely crushing it based on our data. It's both the startup AND enterprise coding tool of choice." 📌 Watch now:
0:46

"Claude Code is the first AI tool that can actually recreate how a data scientist thinks." Here's my new episode with Sumeet Marwaha (Head of Data at Brex) on exactly how to build an AI analyst with Claude Code. We covered: ✅ 3 queries to build a data analyst MCP ✅ How to give the analyst both data + context ✅ Exclusive Brex data on which AI tools are crushing it in startups and enterprise Some quotes from Sumeet: "I've set up dashboards many times in my career. They end up getting ignored. Claude will always read it. Claude will always ask the right questions." "You have to set up Claude Code to not just look at the data. It should be able to search Slack, find the incident, and understand why your metrics look wrong." "This tool is absolutely crushing it based on our data. It's both the startup AND enterprise coding tool of choice." 📌 Watch now:

Peter Yang

39,600 Aufrufe • vor 7 Monaten

Introducing Orchids 1.0 - the first AI app builder to build and deploy any app, any stack (web, mobile, chrome extension, slack bot, AI agent, anything). Use your ChatGPT, Claude Code, Github Copilot, Gemini subscription - or any API key to use models at cost. Comment below to get 100k free credits. Everything you need to build with AI in a single tool.
0:48

Introducing Orchids 1.0 - the first AI app builder to build and deploy any app, any stack (web, mobile, chrome extension, slack bot, AI agent, anything). Use your ChatGPT, Claude Code, Github Copilot, Gemini subscription - or any API key to use models at cost. Comment below to get 100k free credits. Everything you need to build with AI in a single tool.

Bud

355,429 Aufrufe • vor 6 Monaten

🎉 VS Code Day is back! Join us for this free, "Virtually Live" event on April 26, with sessions like: 🤖 AI with GitHub Copilot 🐍 Python 🌐 Remote Development 💻 Accessibility ... & much more! Be a part of the Visual Studio Code story and register today!
0:58

🎉 VS Code Day is back! Join us for this free, "Virtually Live" event on April 26, with sessions like: 🤖 AI with GitHub Copilot 🐍 Python 🌐 Remote Development 💻 Accessibility ... & much more! Be a part of the Visual Studio Code story and register today!

Visual Studio Code

92,083 Aufrufe • vor 3 Jahren

EXCLUSIVE: Microsoft just launched Copilot Vision in Edge—the first AI that can navigate the internet with you in real time. I sat down with Mustafa Suleyman (CEO of Microsoft AI) to discuss how it works, infinite memory, AI companions, agents, and more. Timestamps: 0:00 Intro 0:58 Microsoft Copilot Vision rundown 02:35 Initial reactions and use cases 04:57 How Copilot Vision works 06:02 Teaching AI to remember 08:13 How Microsoft AI is differentiating from OpenAI 09:27 The push for the true AI companion 11:28 Living with a co-intelligence in 10+ years 14:04 How Microsoft handles your data 16:11 When and how can you try Copilot Vision? 18:15 Agentic AI that controls your computer 20:25 What's next: support, gaming, and more 22:34 Preparing the next generation with Copilot 25:11 Mustafa’s advice for students and businesses
26:21

EXCLUSIVE: Microsoft just launched Copilot Vision in Edge—the first AI that can navigate the internet with you in real time. I sat down with Mustafa Suleyman (CEO of Microsoft AI) to discuss how it works, infinite memory, AI companions, agents, and more. Timestamps: 0:00 Intro 0:58 Microsoft Copilot Vision rundown 02:35 Initial reactions and use cases 04:57 How Copilot Vision works 06:02 Teaching AI to remember 08:13 How Microsoft AI is differentiating from OpenAI 09:27 The push for the true AI companion 11:28 Living with a co-intelligence in 10+ years 14:04 How Microsoft handles your data 16:11 When and how can you try Copilot Vision? 18:15 Agentic AI that controls your computer 20:25 What's next: support, gaming, and more 22:34 Preparing the next generation with Copilot 25:11 Mustafa’s advice for students and businesses

Rowan Cheung

268,106 Aufrufe • vor 1 Jahr

How to Create a Professional Data Analysis Report—Even If You’re Not a Data Specialist Today on Agent 101—MuleRun’s first review series where real users test AI agents in real work scenarios—we introduce “Smart Q,” a data analysis expert agent designed to turn anyone into a data-savvy reporter. 1. Team Expertise Smart Q was developed by a team with over 10 years of data analysis experience at a giant corporation. This background ensures that the agent delivers insights and reports that meet professional standards. 2. The Traditional Approach & Its Pain Points Traditionally, creating a data analysis report required deep expertise in tools like Excel, SQL, or Python. You’d need to clean the data, run calculations, generate visualizations, and summarize findings—all of which is time-consuming and prone to human error. For non-specialists, this process is often inaccessible and intimidating. 3. How Smart Q Uses AI—and What Problems It Solves With Smart Q, the entire reporting process is simplified into three steps: upload your raw data, ask a question, and receive charts, key insights, and a polished report—all generated by AI expert. Its key advantages include: ✅Accessibility:No technical background required. ✅Speed:Get a complete analysis in minutes, not hours. ✅Clarity:Receive expert-level conclusions presented in clear, actionable language. Want to become a tester for future AI agents? Engage with this video—comment, like, or share—and we’ll be sure to notice your support! 🎥 See Smart Q in action. #mulerun #mulerun4U #SmartQ
4:11

How to Create a Professional Data Analysis Report—Even If You’re Not a Data Specialist Today on Agent 101—MuleRun’s first review series where real users test AI agents in real work scenarios—we introduce “Smart Q,” a data analysis expert agent designed to turn anyone into a data-savvy reporter. 1. Team Expertise Smart Q was developed by a team with over 10 years of data analysis experience at a giant corporation. This background ensures that the agent delivers insights and reports that meet professional standards. 2. The Traditional Approach & Its Pain Points Traditionally, creating a data analysis report required deep expertise in tools like Excel, SQL, or Python. You’d need to clean the data, run calculations, generate visualizations, and summarize findings—all of which is time-consuming and prone to human error. For non-specialists, this process is often inaccessible and intimidating. 3. How Smart Q Uses AI—and What Problems It Solves With Smart Q, the entire reporting process is simplified into three steps: upload your raw data, ask a question, and receive charts, key insights, and a polished report—all generated by AI expert. Its key advantages include: ✅Accessibility:No technical background required. ✅Speed:Get a complete analysis in minutes, not hours. ✅Clarity:Receive expert-level conclusions presented in clear, actionable language. Want to become a tester for future AI agents? Engage with this video—comment, like, or share—and we’ll be sure to notice your support! 🎥 See Smart Q in action. #mulerun #mulerun4U #SmartQ

MuleRun

30,549 Aufrufe • vor 9 Monaten

New session with Shreya Shankar on How to Automate Evals with AI (correctly) The most important part of the eval workflow is finding issues. Shreya does a live demo of how to steer the AI iteratively to find unknown unknowns Chapter summaries: 00:00:00 Introduction 00:00:55 Why vendors want to automate evals for you 00:01:45 Why no tool can fully automate evals 00:06:00 Mistake #1: Asking AI to just "find the issues" in your data 00:08:11 What good AI-assisted error analysis actually looks like 00:11:12 Live demo: building a review interface from scratch 00:15:10 Annotating traces and building a failure mode taxonomy 00:19:31 Mistake #2: Only reviewing your data once 00:22:53 Mistake #3: Treating all apps with the same accuracy bar 00:25:10 General-purpose agents vs. dedicated eval tools 00:25:48 Summary: three rules for automating evals correctly YT links and more in reply
27:18

New session with Shreya Shankar on How to Automate Evals with AI (correctly) The most important part of the eval workflow is finding issues. Shreya does a live demo of how to steer the AI iteratively to find unknown unknowns Chapter summaries: 00:00:00 Introduction 00:00:55 Why vendors want to automate evals for you 00:01:45 Why no tool can fully automate evals 00:06:00 Mistake #1: Asking AI to just "find the issues" in your data 00:08:11 What good AI-assisted error analysis actually looks like 00:11:12 Live demo: building a review interface from scratch 00:15:10 Annotating traces and building a failure mode taxonomy 00:19:31 Mistake #2: Only reviewing your data once 00:22:53 Mistake #3: Treating all apps with the same accuracy bar 00:25:10 General-purpose agents vs. dedicated eval tools 00:25:48 Summary: three rules for automating evals correctly YT links and more in reply

Hamel Husain

34,196 Aufrufe • vor 1 Monat

🚀Excited to announce Superblocks AI – the AI coding assistant for internal apps! ⚡ Superblocks AI combines the power of the Superblocks drag-and-drop App Builder, with the speed of AI code generation, performance optimization, code explanation, mock data generation, and API call generation across SQL, Python, JavaScript, JSON and HTML. 🐨Our goal at Superblocks has always been to help developers ship mission-critical apps faster to elevate internal operations, and our deeply integrated AI coding assistant does exactly that! Blog:
1:11

🚀Excited to announce Superblocks AI – the AI coding assistant for internal apps! ⚡ Superblocks AI combines the power of the Superblocks drag-and-drop App Builder, with the speed of AI code generation, performance optimization, code explanation, mock data generation, and API call generation across SQL, Python, JavaScript, JSON and HTML. 🐨Our goal at Superblocks has always been to help developers ship mission-critical apps faster to elevate internal operations, and our deeply integrated AI coding assistant does exactly that! Blog:

Brad Menezes

73,251 Aufrufe • vor 3 Jahren