Video yükleniyor...

Video Yüklenemedi

Bu video yüklenirken bir sorun oluştu. Bu geçici bir ağ sorunundan kaynaklanıyor olabilir veya video kullanılamıyor olabilir.

Ana Sayfaya Dön

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... show more

Matt Dancho (Business Science)

103,862 subscribers

85,464 görüntüleme • 10 ay önce •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

12 Yorum

Matt Dancho (Business Science) profil fotoğrafı

Matt Dancho (Business Science)10 ay önce

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

Quintin Tyree profil fotoğrafı

Quintin Tyree10 ay önce

Awesome. This can go in so many different directions! Having a tab with live figures and updated table would be nice to toggle between! Excited to follow along

Matt Dancho (Business Science) profil fotoğrafı

Matt Dancho (Business Science)10 ay önce

Yes. Please make requests on GitHub.

Aditya profil fotoğrafı

Aditya10 ay önce

AI Council and now this, we are truly living in the agentic AI era.

⚡️Boltbet⚡️ profil fotoğrafı

⚡️Boltbet⚡️10 ay önce

⚡️⚡️❤️

FrostByte profil fotoğrafı

FrostByte10 ay önce

this is excellent work

Matt Dancho (Business Science) profil fotoğrafı

Matt Dancho (Business Science)10 ay önce

Thank you!

Preet profil fotoğrafı

Preet10 ay önce

Very impressive. Reproducibility + automated cleaning is the hardest part to get right—how does it handle edge cases like mixed dtypes, outliers, or domain-specific cleaning rules?”

Suhrab Khan⚡️ profil fotoğrafı

Suhrab Khan⚡️10 ay önce

This open-source AI data science team is a game-changer! Fully automating the workflow from cleaning to feature engineering while keeping everything reproducible is exactly what many teams have been waiting for.

Ramsha profil fotoğrafı

Ramsha9 ay önce

Ok

Chuck Petras profil fotoğrafı

Chuck Petras10 ay önce

@BrianRoemmele

sasha.nothing(🪞,🪞) profil fotoğrafı

sasha.nothing(🪞,🪞)10 ay önce

Noice, any Plan for time series analysis agents🫡

Benzer Videolar

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):

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 görüntüleme • 1 yıl önce

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:

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)

50,841 görüntüleme • 1 yıl önce

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):

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 görüntüleme • 1 yıl önce

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):

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)

31,125 görüntüleme • 1 yıl önce

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):

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 görüntüleme • 1 yıl önce

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 GitHub. I'll guide you through setting up the Copilot app, creating dozens of data analysis charts from any CSV or Excel file, and interacting with your data live. This AI is a BIG help! Table of Contents: 00:00 Introduction to the App 02:24 Setting Up the App 04:25 Using the App 08:58 Understanding the Python Code Github to AI Data Science Team (app is in the apps folder): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter: === Want to learn how to build AI projects companies actually want? (live Python Code) On Wednesday, April 9th, I'm sharing one of my best AI Projects: Time Series Forecasting with AI Register here (500 Seats):

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 GitHub. I'll guide you through setting up the Copilot app, creating dozens of data analysis charts from any CSV or Excel file, and interacting with your data live. This AI is a BIG help! Table of Contents: 00:00 Introduction to the App 02:24 Setting Up the App 04:25 Using the App 08:58 Understanding the Python Code Github to AI Data Science Team (app is in the apps folder): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter: === Want to learn how to build AI projects companies actually want? (live Python Code) On Wednesday, April 9th, I'm sharing one of my best AI Projects: Time Series Forecasting with AI Register here (500 Seats):

Matt Dancho (Business Science)

12,736 görüntüleme • 1 yıl önce

देश का AI talent pool विकसित करने में data science, AI engineering और data analytics जैसे skills की प्रभावी भूमिका होगी।

देश का AI talent pool विकसित करने में data science, AI engineering और data analytics जैसे skills की प्रभावी भूमिका होगी।

President of India

43,876 görüntüleme • 10 ay önce

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):

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)

77,564 görüntüleme • 1 yıl önce

is building full-stack data science AI agents that turn raw data into insights and answers in minutes, not days. Putting the power of data-driven decisions into anyone's hands. Congrats on the launch, matin and @whyispaper!

is building full-stack data science AI agents that turn raw data into insights and answers in minutes, not days. Putting the power of data-driven decisions into anyone's hands. Congrats on the launch, matin and @whyispaper!

Y Combinator

30,324 görüntüleme • 1 yıl önce

A new era in Data Science is here 🚀. Say hello to your Chief AI Chat Data Scientist! From this day forward, advanced analytics and automated data workflows are within anyone's reach. We like to call it "Freedom To Create".

A new era in Data Science is here 🚀. Say hello to your Chief AI Chat Data Scientist! From this day forward, advanced analytics and automated data workflows are within anyone's reach. We like to call it "Freedom To Create".

Carlos Mendez

5,546,398 görüntüleme • 3 yıl önce

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

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 görüntüleme • 1 yıl önce

Perplexity Computer can now use Snowflake as a data source and work as a personal Data Science team if you are on Snowflake And the Data Analytics team as well 👀

Perplexity Computer can now use Snowflake as a data source and work as a personal Data Science team if you are on Snowflake And the Data Analytics team as well 👀

🚨 AI News | TestingCatalog

20,048 görüntüleme • 5 ay önce

Balancing a 9-5 job with dreams of a Data Science career? 📊 Our Part-time Data Science program has you covered! Learn Python for Data Science in just 35 weeks. Enroll now for our February 2024 class. Your journey into the world of Data begins with us! Apply Now!🚀 #DataScience

Balancing a 9-5 job with dreams of a Data Science career? 📊 Our Part-time Data Science program has you covered! Learn Python for Data Science in just 35 weeks. Enroll now for our February 2024 class. Your journey into the world of Data begins with us! Apply Now!🚀 #DataScience

Moringa School

4,530,436 görüntüleme • 2 yıl önce

"Data science has changed #politics and there's no going back" Our BSc in Politics and Data Science trains students for the next generation of challenges as #BigData, #SocialMedia and #AI rapidly transform politics and society. Find out more 👉

"Data science has changed #politics and there's no going back" Our BSc in Politics and Data Science trains students for the next generation of challenges as #BigData, #SocialMedia and #AI rapidly transform politics and society. Find out more 👉

LSE Government

13,516 görüntüleme • 3 yıl önce

AI is changing what data teams are expected to build. Increasingly, the focus is on AI applications, agents, and automations that turn data into action. That’s why founder Zach Wilson is launching a free six-hour Databricks boot camp starting August 3, covering: • Building data systems with Lakebase and Postgres • Working with unstructured data, vector search, and retrieval • Building AI agents with Agent Bricks The course runs entirely in Databricks Free Edition and is designed for beginners and practitioners building practical AI data engineering skills. Join here:

AI is changing what data teams are expected to build. Increasingly, the focus is on AI applications, agents, and automations that turn data into action. That’s why founder Zach Wilson is launching a free six-hour Databricks boot camp starting August 3, covering: • Building data systems with Lakebase and Postgres • Working with unstructured data, vector search, and retrieval • Building AI agents with Agent Bricks The course runs entirely in Databricks Free Edition and is designed for beginners and practitioners building practical AI data engineering skills. Join here:

Databricks

21,458 görüntüleme • 2 ay önce

I built an AI data visualization Agent. The AI Agent can automatically generate the code and visualize the data using code interpreter sandbox. 100% Opensource Code with step-by-step tutorial.

I built an AI data visualization Agent. The AI Agent can automatically generate the code and visualize the data using code interpreter sandbox. 100% Opensource Code with step-by-step tutorial.

Shubham Saboo

68,488 görüntüleme • 1 yıl önce

Computer now connects to Snowflake. Run end-to-end work against live warehouse data and get answers with SQL, source tables, filters, and metrics. It’s like a personal data science team, on call with accurate answers from live company data.

Computer now connects to Snowflake. Run end-to-end work against live warehouse data and get answers with SQL, source tables, filters, and metrics. It’s like a personal data science team, on call with accurate answers from live company data.

Perplexity

80,491 görüntüleme • 5 ay önce

This is freaking huge.. AIPOCH just dropped .science.. It bundles your code, data, AI conversations, python envs, and literature PDFs into one portable session anyone can fork. Here’s how it works:

This is freaking huge.. AIPOCH just dropped .science.. It bundles your code, data, AI conversations, python envs, and literature PDFs into one portable session anyone can fork. Here’s how it works:

ɱҽԃι✨

16,174 görüntüleme • 13 gün önce