DataFramed

#44 Project Jupyter and Interactive Computing

Oct 15, 2018
Ask episode
Chapters
Transcript
Episode notes
1
Introduction
00:00 • 2min
2
Data Framed - What's the Big Thing About You?
02:01 • 2min
3
What Skills Do You Need to Do a Project in Java?
03:53 • 2min
4
Data Camp
06:14 • 2min
5
How Did You Get Into Data Science?
07:49 • 2min
6
Project Jupiter - What Is It?
09:42 • 2min
7
The Interaction Between Python and Python
11:15 • 2min
8
The Scale and Reach of Project Jupiter
13:27 • 4min
9
Jupiter Steering Council - What Is the Right Narrative?
17:40 • 2min
10
What Are Good Ways to Get Involved in Open Source Contributions?
19:43 • 5min
11
Can Humans Multi Task, but Machines Can
24:23 • 3min
12
How to Use Maltitas Learning in Machine Learning?
27:24 • 2min
13
Data Science and Machine Learning - What Are the Main Uses of Jupiter Notebooks?
29:16 • 2min
14
The Scale of Jupiter Notebooks Is Getting Larger
31:32 • 4min
15
What Is the Most Surprising Use of a Jupiter Notebook?
35:17 • 2min
16
What's Up With the Open Source Project?
37:09 • 2min
17
Is There a Need for Jupiter Note Books?
39:06 • 3min
18
Project Jupiter Notebooks - I Don't Like Notebooks
42:21 • 1min
19
Why Multi Task Learning Is So Effective?
43:49 • 4min
20
The Next Generation Useor Inter Face for Project Jupiter
47:25 • 4min
21
Using Jupiter Lab's File System Axis
51:10 • 3min
22
Using a Viewer to View Large Datasets
53:40 • 2min
23
Using Jupiter Lab to Collaborate on Notes
55:51 • 2min
24
The Challenges of the Project Jupiter Hub?
57:34 • 3min
25
The Call to Action for Open Source Projects
01:00:23 • 2min
26
Open Source Data Tooling Forms
01:02:18 • 3min