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Schwarzwald_AI
Schwarzwald_AI

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How many Facebook friends will you have? Linear Regression has the answer.

Table of Contents 1 Executive Summary 2 Introduction 3 Methodology 4 Results 5 Discussion 6 Conclusion 1 Executive Summary This case study will model the number of friends using Linear Regression using a relatively small dataset. We will see the importance of feature selection, review the essential assumptions about the data for linear regression, and apply…

Data Science

8 min read

How many Facebook friends will you have? Linear Regression has the answer.
How many Facebook friends will you have? Linear Regression has the answer.
Data Science

8 min read


Aug 22, 2021

How to Predict Customer Churn using Machine Learning? A Telecom Case Study

Table of Contents 1 Executive Summary 2 Introduction 3 Methodology 4 Results 5 Discussion 6 Conclusion Appendixes 1 Executive Summary We will build a predictive model for a telecom customer churn using variables from the customer dataset. …

Data Science

11 min read

How to Predict Customer Churn using Machine Learning? A Telecom Case Study
How to Predict Customer Churn using Machine Learning? A Telecom Case Study
Data Science

11 min read


Published in

MLearning.ai

·Aug 16, 2021

How to Forecast Customer Sales Volume Using Machine Learning?

Contents: Executive Summary Introduction Methodology Results Discussion Conclusion Appendixes 1. EXECUTIVE SUMMARY In this article, we will see how to predict customer sales volume using transaction history and demographics datasets. We conclude that a Simple Linear Regression could use annual income as a strong predictor for future sales. 2. INTRODUCTION This case study is part…

Data Science

6 min read

How to Forecast Customer Sales Volume Using Machine Learning?
How to Forecast Customer Sales Volume Using Machine Learning?
Data Science

6 min read


Aug 14, 2021

Using Anomaly Detection Techniques to Spot Credit Card Fraud

Table of Contents Executive Summary Introduction Methodology Results Discussion Conclusion 1 Executive Summary This article illustrates an example of anomaly detection techniques application to analyze customer credit card behavior to identify potentially fraudulent transactions. We discuss the preprocessing steps, apply anomaly detection algorithms such as Local Outlier Factor and Elliptic Envelope hyper-parameters, and visualize the outcome.

Data Science

5 min read

Using Anomaly Detection Techniques to Spot Credit Card Fraud
Using Anomaly Detection Techniques to Spot Credit Card Fraud
Data Science

5 min read


Mar 7, 2021

Predicting New York City 311 Service Requests

IBM DS0720EN DATA SCIENCE AND MACHINE LEARNING CAPSTONE PROJECT — ABSTRACT

Machine Learning

18 min read

Predicting New York City 311 Service Requests
Predicting New York City 311 Service Requests
Machine Learning

18 min read

Schwarzwald_AI

Schwarzwald_AI

13 Followers

Data Science | Machine Learning | Operations Research

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