Predict fraud with data visualization & predictive modeling!

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

3.90 (130 reviews)
Udemy
platform
English
language
Programming Languages
category
1,375
students
9 hours
content
Jan 2019
last update
$49.99
regular price

What you will learn

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!

Description

"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." ⭐ ⭐ ⭐ ⭐ ⭐ 

"Incredible course. Looking forward for more content like this. Thank you and good job." - Joniel G.

"Makes learning Python interesting and quick."

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Do you want to learn how to use Artificial Intelligence (AI) for automation? In this course, we cover coding in Python, working with TensorFlow, and analyzing credit card fraud. We interweave theory with practical examples so that you learn by doing.

This course was funded by a wildly successful Kickstarter.

AI is code that mimics certain tasks. You can use AI to predict trends like the stock market. Automating tasks has exploded in popularity since TensorFlow became available to the public (like you and me!) AI like TensorFlow is great for automated tasks including facial recognition. One farmer used the machine model to pick cucumbers! 

Join Mammoth Interactive in this course, where we blend theoretical knowledge with hands-on coding projects to teach you everything you need to know as a beginner to credit card fraud detection.

Enroll today to join the Mammoth community!

Content

Introduction

What is Python Artificial Intelligence?

Python Basics

Installing Python and PyCharm
Got a Python problem or question?
How to use PyCharm
Introduction and Variables
Multivalue Variables
Control Flow
Functions
Classes and Wrapup
Source Files

TensorFlow Basics

Installing TensorFlow
Introduction and Setup
FAQ: Help with TensorFlow Installation
What is TensorFlow?
Constant and Operation Nodes
Placeholder Nodes
Variable Nodes
How to Create a Regression Model
Building Linear Regression
Source Files

Fraud Detection (Credit Card)

Introduction
New Location to Download Dataset
Project Overview
Introducing a Dataset
Building Training: Testing Datasets
Eliminating Dataset Bias
Building a Computational Graph
Building Functions to Connect Graph
Training the Model
Testing the Model
Source Files

Bootcamp Peek! Machine Learning Neural Networks

Introduction to Machine Learning Neural Networks
Introduction to Machine Learning
Introduction to Neutral Networks
Introduction to Convolutions

Explore the Keras API

Introduction to the Keras API
Introduction to TensorFlow and Keras
Understanding Keras Syntax
Introduction to Activation Functions

Format Datasets and Examine CIFAR-10

Introduction to Datasets and CIFAR-10
Exploring CIFAR-10 Dataset
Understanding Specific Data Points
Formatting Input Images

Build an Image Classifier Model

Introduction to the Image Classifier Model
Building the Model
Compiling and Training the Model
Gradient Descent and Optimizer

Save and Load Trained Models

Introduction to Saving and Loading
Saving and Loading Model to H5
Saving Model to Protobuf File
Bonus Summary

Bonus Sections Source Material

Texts Assets: Understand Machine Learning Neural Networks
Texts Assets: Explore the Keras API
Asset Files: Format Datasets and Examine CIFAR-10
Asset Files: Build the Image Classifier Model
Asset Files: Save and Load Trained Models

Resources

Bonus Lecture: Get 155 courses!
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Screenshots

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Reviews

Subhash
January 3, 2021
Pros: 1. Quick learning of Python and exercises to keep engaged 2. You get a fair idea of Image Classifier using ML technique Cons: 1. Course is outdated as it refers to Tensorflow 1 while the latest is 2. You need to modify the given code to make it work and nobody is telling you upfront. 2. The title of this course is misleading. I wanted to learn the case study of credit card fraud but it gives no information on the basis of data we are doing dealing with. You will end up learning more Image Processing than financial fraud. 3. Sometimes the trainer talks more than actually required. 4. Installing Tensorflow was a nightmare Recommend to learn Data Science prior to learning ML since all the processing that takes place here is based on what data we are dealing with. It wont make much sense without knowing why those ML techniques are used for the given data.
Joe
July 31, 2020
Great content and a great voice behind the explanations. The only critique I have is that some of the material/code needs a slight update for TensorFlow2.3+. That being said just running everything in compat.mode for TF1.0+ works great!
Christopher
May 4, 2020
Useful and practical, with knowledge from beginner to expert. Easily skip over sections you are already comfortable with, or revisit sections you need to understand more.
Anurag
March 21, 2018
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. Just 1 humble suggestion: Have a small section for neural networks too, before diving into fraud detection application. Just about 15 minutes of so, should suffice. Thank you for the great course. Regards
PREETI
January 12, 2018
videos are unnecessarily long... especially intro videos, dataset intro... by the time I am reaching main content I feel already tired and a little bored..... sorry for this feedback I haven't reached the main content yet but I would have loved if there wasn't too much talking in the intro videos of every section.
Raymond
December 21, 2017
I like this course, it is very practical with a real project and working code, the only thing that is missing to me is there is no (or no detailed) explanation to the multiple layer neuro model, but I guess that is because the course does require some preliminary knowledge on Neuro model. If the course can include a pre-requisite requirement slide, and maybe recommend some courses, that would make this course perfect. Thanks

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1426076
udemy ID
11/8/2017
course created date
1/18/2020
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