Finding Actionable Insights using Keras Autoencoders
Using Autoencoders to Better Understand your Customers - Measuring Customer Credit Risk
4.50 (79 reviews)
3,484
students
1 hour
content
Apr 2020
last update
FREE
regular price
What you will learn
Learn to build a Keras Autoencoder using Python
Learn to extract actionable insights from data using unsupervised and semi-supervised modeling
Learn to find anomalies in data
Description
Please join me for another exciting data science class where we apply autoencoders or unsupervised learning towards the pursuit of knowledge.
Remember at the end of the day modeling and data science don't mean much if we can't extract actual insights to help guide our customers, our friends, the research community in the advancement of whatever it is they are after using data. Autoencoders can help you better understand your data, answer your questions, and even discover new ones! Please join me on this exciting adventure!
Content
Introduction
Introduction
About me
What is an Autoencoder and what is it good for?
Preparing the Open Source Statlog - German Credit Data
Quick classification look with AutoML
Building our Keras Autoencoder
Investigating anomalies
Screenshots
Reviews
Ömer
April 13, 2022
sanırım süreye sığdırmak için hızlıca anlatmış
ancak içinde çok kıymetli bilgiler var, dikkatli dinlemek gerekiyor.
sadece "autoencoder" merak edenlerin değil
veri bilimci olmak isteyen herkesin mutlaka alması gereken bir kurs
çok başarılı
Vytautas
October 6, 2021
Yes, looks like an efficient use of my time. Getting stuck into things without spending ages on elimentary matters.
Pablo
October 31, 2020
Very easy to follow and a good motivation to start looking at auto-encoders now that I understand better a way to interpret their results.
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2925788
udemy ID
3/28/2020
course created date
4/9/2020
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