Comparing Haskell to R with Will Kurt

1

Introduction

00:00 • 4min

2

How to Write a Book in Haskell

03:54 • 6min

3

Python and the Stats Ecosystem

09:28 • 3min

4

Python Over R for Machine Learning Platforms

12:48 • 4min

5

How to Type Objects in JavaScript

16:52 • 2min

6

The Differences Between JavaScript and Data Science

18:33 • 4min

7

The Importance of Type Checking in Data Science

22:54 • 3min

8

The Difference Between Static Typing and Dynamic Typing

26:17 • 4min

9

How to Think About Workflows in Programming

30:23 • 3min

10

The Importance of Reusing Functions in Notebooks

33:31 • 4min

11

The Future of Programming Languages

37:48 • 2min

12

The Future of Languages

39:48 • 5min

13

The New Categorization of High Reliability Tools

44:43 • 3min

14

The Importance of Reliability in AI

48:01 • 2min

15

The Importance of a Soft Template in Data Science Workflows

49:38 • 2min

16

Differentiable Programming: A Cool Approach to Problem Solving

51:47 • 4min

17

The Importance of Gradient Derivatives in Programming

55:42 • 2min

18

The Future of Machine Learning

58:03 • 2min