Predict fraud with data visualization & predictive modeling!

Create a credit card fraud detection model! Learn predictive modeling, logistic regression, and regression analysis.
4.10 (133 reviews)
Udemy
platform
English
language
Programming Languages
category
Predict fraud with data visualization & predictive modeling!
1 411
students
9 hours
content
Jan 2019
last update
$19.99
regular price

Why take this course?


🎓 Course Title: Predict Fraud with Data Visualization & Predictive Modeling!

🚀 Course Headline: Create a Credit Card Fraud Detection Model! Learn Predictive Modeling, Logistic Regression, and Regression Analysis.


"There are not that many tutorials on PyCharm. In fact, hardly any. Because of this one, I got my first broad overview of not only PyCharm, but also TensorFlow. Bottom-line: It's a great value for money." ⭐ ⭐ ⭐ ⭐


🔍 Course Description:

Are you intrigued by the power of Artificial Intelligence (AI) to predict complex patterns and automate tasks? Do you want to delve into the world of credit card fraud detection using AI? If your answer is a resounding 'Yes!', then our online course at Mammoth Interactive is your gateway to mastering this cutting-edge field.

Why This Course? This course was made possible through the support of a successful Kickstarter campaign, which speaks volumes about its potential and value. It's not just about learning theoretical concepts; it's about immersing yourself in hands-on coding projects that will transform your understanding of AI.

🚀 What You'll Learn:

  • Python Coding: Dive into Python, the versatile programming language that is the backbone of AI and machine learning.
  • TensorFlow Mastery: Get to grips with TensorFlow, Google's open-source machine learning framework that has revolutionized AI.
  • Data Visualization Techniques: Learn to represent complex datasets in a more understandable form, helping you to visualize trends and patterns.
  • Predictive Modeling: Understand and apply predictive modeling techniques to anticipate fraudulent transactions with remarkable accuracy.
  • Logistic Regression: Discover how logistic regression can classify data into different categories, particularly useful in credit card fraud detection.
  • Regression Analysis: Explore the methods used to analyze relationships between variables, which is key to predicting outcomes in AI.

🤖 The World of AI:

AI isn't just for tech giants and data scientists. It's a tool that can be harnessed by anyone interested in automation, from recognizing faces to detecting fraudulent transactions. In this course, you'll learn how AI like TensorFlow is changing the game across various industries.

🌍 Join the Community:

By enrolling in this course, you're not just learning a skill—you're joining a community of forward-thinking individuals who are passionate about the potential of AI. With Mammoth Interactive, you'll blend theoretical knowledge with hands-on coding projects, ensuring that by the end of the course, you'll be confident in your ability to create models that predict fraud and much more.

📆 Enroll Now:

Don't miss out on this opportunity to shape your future in AI. Enroll today and take the first step towards becoming a data visualization and predictive modeling expert. Let's embark on this journey together and unlock the potential of AI!


Key Takeaways:

  • Comprehensive Learning: Combines theoretical knowledge with practical coding projects.
  • Expert Guidance: Led by industry professionals with real-world experience in AI and machine learning.
  • Cutting-Edge Techniques: Teaches you the latest tools and methods in data visualization and predictive modeling.
  • Real-World Application: Offers insights into how AI can be applied to real-world problems like credit card fraud detection.
  • Community Support: Joins you with a community of learners who are equally passionate about AI's potential.

👉 Ready to get started? Click enroll and take the first step towards mastering predictive modeling and data visualization for fraud detection today!

Course Gallery

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1426076
udemy ID
08/11/2017
course created date
18/01/2020
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