Predict fraud with data visualization & predictive modeling!

Online Course

Udemy
Predict fraud with data visualization & predictive modeling!

What is the course about?

Predict fraud with data visualization & predictive modeling!
The course Predict fraud with data visualization & predictive modeling! is an online class provided by Udemy. It may be possible to receive a verified certification or use the course to prepare for a degree.

Create a credit card fraud detection model! Learn predictive modeling, logistic regression, and regression analysis.

Course description
  • Predict fraud with data visualization & predictive modeling!
  • Learn how to code in Python, a popular coding language used for websites like YouTube and Instagram.
  • Learn TensorFlow and how to build models of linear regression
  • Make a Credit Card Fraud Detection Model in Python. Learn how to keep your data safe!
  • Please download PyCharm Community Edition 2017.2.3.
  • 9 hours on-demand video
  • 14 articles
  • 8 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
  • Mammoth Interactive

Prerequisites & Facts

Predict fraud with data visualization & predictive modeling!

Course Topic

Development, Fraud Analytics, Programming Languages

University, College, Institution

Udemy

Course Skill Level

Course Language

English

Place of class

Online, self-paced (see curriculum for more information)

Degree

Certificate

Degree & Cost

Predict fraud with data visualization & predictive modeling!

To obtain a verified certificate from Udemy you have to finish this course or the latest version of it, if there is a new edition. The class may be free of charge, but there could be some cost to receive a verified certificate or to access the learning materials. The specifics of the course may have been changed, please consult the provider to get the latest quotes and news.
Udemy
Predict fraud with data visualization & predictive modeling!
provided by Udemy

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School: Udemy
Topic: Development, Fraud Analytics, Programming Languages