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Finding Actionable Insights using Keras Autoencoders

  • Development
  • Jan 16, 2025
SynopsisFinding Actionable Insights using Keras Autoencoders, availab...
Finding Actionable Insights using Keras Autoencoders  No.1

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

  • Finding Actionable Insights using Keras Autoencoders  No.2
    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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