#410: The Intersection of Tabular Data and Generative AI

1

Introduction

00:00 • 2min

2

How I Got Into Programming in Python and AI

01:38 • 2min

3

The Evolution of Python and C++

03:27 • 2min

4

The Future of AI

05:23 • 2min

5

The Benefits of Faster GPUs

07:52 • 4min

6

Chat GPT: How to Avoid Deep Nested Codes

11:31 • 4min

7

How to Download Stuff Concurrently Using a Particular Library in Flutter

15:24 • 3min

8

Chatsy P: A Quick AI Project Sketch

18:22 • 2min

9

Chatshi Dppies and GitHub Co-Pilot

20:19 • 2min

10

The Ethics of AI

21:58 • 3min

11

The Power of Accelerant

24:35 • 2min

12

Sketch: A Proximate Lab for Data Analysis

26:14 • 2min

13

How to Combine Data Sketches With AI

27:52 • 2min

14

Sketch: A Proof of Concept for Chatbots

29:54 • 2min

15

How to Ask Pandas Data Frame Questions

31:26 • 2min

16

Python Bytes: A GUI Framework for Python

33:08 • 2min

17

How to Open AI Specific Completion Endpoints

35:12 • 2min

18

How to Scale Your Python Web Apps Faster

36:54 • 2min

19

How to Create Derivative Features From Sales Data Dot Sketch Dot

38:28 • 3min

20

How to Train a Model to Predict Sales for the Next Six Months

40:59 • 3min

21

Open AI: A Lightweight Way to Extract Data From Model Weights

44:10 • 2min

22

The Future of AI

45:48 • 2min

23

How to Use Sketch to Improve Performance

47:52 • 2min

24

The Privacy Implications of Asking Questions About Your Data

49:34 • 2min

25

The Future of APIs

51:58 • 3min

26

How to Write a Function in Python

54:56 • 2min

27

How to Make a Conversation With a Bot

56:57 • 3min

28

Python Python Editor

59:38 • 2min

29

The Future of AI and Tabular Data

01:01:34 • 2min

30

How to Get Started With Python

01:03:18 • 2min