Finding Actionable Insights using Keras Autoencoders

Finding Actionable Insights using Keras Autoencoders, available at Free, has an average rating of 4.55, with 7 lectures, based on 80 reviews, and has 3566 subscribers.

You will learn about 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 This course is ideal for individuals who are Anybody wanting to analyze data or Anybody wanting to perform anomaly detection or Anybody interested in Autoencoders and machine learning with Keras It is particularly useful for Anybody wanting to analyze data or Anybody wanting to perform anomaly detection or Anybody interested in Autoencoders and machine learning with Keras.

Enroll now: Finding Actionable Insights using Keras Autoencoders

Summary

Title: Finding Actionable Insights using Keras Autoencoders

Price: Free

Average Rating: 4.55

Number of Lectures: 7

Number of Published Lectures: 7

Number of Curriculum Items: 7

Number of Published Curriculum Objects: 7

Original Price: Free

Quality Status: approved

Status: Live

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

Who Should Attend

Anybody wanting to analyze data
Anybody wanting to perform anomaly detection
Anybody interested in Autoencoders and machine learning with Keras

Target Audiences

Anybody wanting to analyze data
Anybody wanting to perform anomaly detection
Anybody interested in Autoencoders and machine learning with Keras

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!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: About me

Lecture 3: What is an Autoencoder and what is it good for?

Lecture 4: Preparing the Open Source Statlog - German Credit Data

Lecture 5: Quick classification look with AutoML

Lecture 6: Building our Keras Autoencoder

Lecture 7: Investigating anomalies

Instructors

Manuel Amunategui
Data Scientist & Quantitative Developer

Rating Distribution

1 stars: 1 votes
2 stars: 1 votes
3 stars: 9 votes
4 stars: 33 votes
5 stars: 36 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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