S1 E2 Tuning Neural Networks Normalization, Output Functions and Loss Functions

Webseries #1: Comprehensive and Intuitive Introduction to Deep Learning -- Numbers and Text by ‪@parthaseetala‬

SEASON 1 - EPISODE 2:

In this episode we'll learn about Input Normalization techniques and go through several use cases that can be solved using Deep Learning techniques. The use cases covered are -- (1) Regression, (2) Binary Classification, (3) Multi-class Classification, (4) Multi-label Classification, (5) Ranking

CHAPTERS

00:00:00   Introduction to Season 1 Episode 2
00:00:39   Tuning Input Layer -- Normalization
00:13:44  Tuning Output Layer
00:16:01  Use cases that can be solved using Deep Neural Networks
00:19:12  Regression use case overview
00:12:56  Single-output Regression use case
00:24:48  Multi-output Regression use case
00:45:41  Binary Classification use case
01:08:01  Multi-class Classification use case
01:26:06  Multi-label Classification use case
01:58:45  Ranking use case
02:23:57  Summary -- Cheat sheet for mapping Output/Loss functions to their respective use cases
02:25:39  Preview of next episode Season 1 Episode 3

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