Chapters
Transcript
Episode notes
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Introduction
00:00 • 2min
What Is Zips Law?
01:59 • 2min
What's the Difference Between Perceptron and Bays?
03:37 • 2min
How to Learn a Text, Vido and Beding Using Narratives
05:08 • 5min
Machine Translation - A Time When Language Wasn't Something Computers Were Good At
10:22 • 2min
The Future of Data Science With Text Mining
11:59 • 2min
Using Per Learning to Classify Phonics of Endangered Languages
13:42 • 2min
Deep Learning and Machine Learning for Under Resourced Languages
15:23 • 2min
Authorship Attribution
16:57 • 2min
Ylometric Cues for Machine Translation
18:30 • 2min
Using the Word to Vec in a Machine Learning Architecture
20:13 • 2min
Machine Learning
21:56 • 2min
The Problem of Short Text Matching
23:50 • 2min
The Importance of Transfer Learning in Machine Learning
25:28 • 2min
BERF - A Neural Network for Machine Learning
27:20 • 2min
How to Improve the Performance of Training Data and Testing Data With Deep Learning
29:07 • 2min
Can Deep Learning Be Learned?
31:11 • 2min
How Good Is This Model Really?
32:54 • 2min
The Power of Deep Learning
34:39 • 2min
Onyx for Machine Learning Models
36:19 • 2min