Artificial Intelligence in Business Management Machine Learning Foundations Methodologies and Applications 1st Edition by Teik Toe Teoh, Yu Jin Goh 98199455779789819945573

Part I Artificial Intelligence Algorithms

1 Introduction to Artificial Intelligence

1.1 Introduction

1.2 History of Artificial Intelligence

1.3 Types of Artificial Intelligence Algorithms

1.4 Organization of the Book

References

2 Regression

2.1 Linear Regression

2.2 Decision Tree Regression

2.3 Random Forests

2.4 Neural Network

2.5 Improving Regression Performance

2.5.1 Boxplot

2.5.2 Remove Outlier

2.5.3 Remove NA

2.5.4 Feature Importance

Exercises

References

3 Classification

3.1 Logistic Regression

3.2 Decision Tree and Random Forest

3.3 Neural Network

3.4 Support Vector Machines

3.4.1 Important Hyperparameters

3.5 Naive Bayes

3.6 Improving Classification Performance

Exercises

References

4 Clustering

4.1 Introduction to Clustering

4.2 K-means

4.3 The Elbow Method

Exercises

References

5 Time Series

5.1 Introduction to Time Series

5.2 Stationarity

5.3 Level, Trend, and Seasonality

5.4 Exponential Smoothing

5.4.1 Simple Exponential Smoothing

5.4.2 Double Exponential Smoothing (Holt’s Exponential Smoothing)

5.4.3 Triple Exponential Smoothing (Holt–Winters Exponential Smoothing)

5.5 Moving Average Smoothing

5.6 Autoregression

5.7 Moving Average Process

5.8 SARIMA

5.9 ARCH/GARCH

Exercises

References

6 Convolutional Neural Networks

6.1 The Convolution Operation

6.2 Pooling

6.3 Flattening

6.4 Building a CNN

6.5 CNN Architectures

6.5.1 VGG16

6.5.2 InceptionNet

6.5.3 ResNet

6.6 Finetuning

6.7 Other Tasks That Use CNNs

6.7.1 Object Detection

6.7.2 Semantic Segmentation

Exercises

References

7 Text Mining

7.1 Preparing the Data

7.2 Texts for Classification

7.3 Vectorize

7.4 TF-IDF

7.5 Web Scraping

7.6 Tokenization

7.7 Part of Speech Tagging

7.8 Stemming and Lemmatization

Exercises

Reference

8 Chatbot, Speech, and NLP

8.1 Speech to Text

8.2 Preparing the Data for Chatbot

8.2.1 Download the Data

8.2.2 Reading the Data from the Files

8.2.3 Preparing Data for Seq2Seq Model

8.3 Defining the Encoder–Decoder Model

8.4 Training the Model

8.5 Defining Inference Models

8.6 Talking with Our Chatbot

Exercises

References

Part II Applications of Artificial Intelligence in Business Management

9 AI in Human Resource Management

9.1 Introduction to Human Resource Management

9.2 Artificial Intelligence in Human Resources

9.3 Applications of AI in Human Resources

9.3.1 Salary Prediction

9.3.2 Recruitment

9.3.3 Course Recommendation

9.3.4 Employee Attrition Prediction

Exercises

References

10 AI in Sales

10.1 Introduction to Sales

10.1.1 The Sales Cycle

10.2 Artificial Intelligence in Sales

10.3 Applications of AI in Sales

10.3.1 Lead Scoring

10.3.2 Sales Assistant Chatbot

10.3.3 Product Recommender Systems

10.3.4 Recommending via Pairwise Correlated Purchases

Exercises

References

11 AI in Marketing

11.1 Introduction to Marketing

11.1.1 Sales vs Marketing

11.2 Artificial Intelligence in Marketing

11.3 Applications of AI in Marketing

11.3.1 Customer Segmentation

11.3.2 Analyzing Brand Associations

Exercises

References

12 AI in Supply Chain Management

12.1 Introduction to Supply Chain Management

12.1.1 Supply Chain Definition

12.1.2 Types of Supply Chain Models

12.1.3 Bullwhip Effect

12.1.4 Causes of Variation in Orders

12.1.5 Reducing the Bullwhip Effect

12.2 Artificial Intelligence in Supply Chain Management

12.3 Applications of AI in Supply Chain Management

12.3.1 Demand Forecasting with Anomaly Detection

12.3.2 Quality Assurance

12.3.3 Estimating Delivery Time

12.3.4 Delivery Optimization

Exercises

References

13 AI in Operations Management

13.1 Introduction to Operations Management

13.1.1 Business Process Management

13.1.2 Six Sigma

13.1.3 Supply Chain Management (SCM) vs. Operations Management (OM)

13.2 Artificial Intelligence in Operations Management

13.3 Applications of AI in Operations

13.3.1 Root Cause Analysis for IT Operations

13.3.2 Predictive Maintenance

13.3.3 Process Automation

Exercises

References

14 AI in Corporate Finance

14.1 Introduction to Corporate Finance

14.2 Artificial Intelligence in Finance

14.3 Applications of AI in Corporate Finance

14.3.1 Default Prediction

14.3.2 Predicting Credit Card Fraud

Exercises

References

15 AI in Business Law

15.1 Introduction to Business Law

15.1.1 Types of Businesses

15.1.2 Types of Business Laws

15.2 Artificial Intelligence in Business Law

15.3 Applications of AI in Business Law

15.3.1 Legal Document Summarization

15.3.2 Contract Review Assistant

15.3.3 Legal Research Assistant

Exercises

References

16 AI in Business Strategy

16.1 Introduction to Business Strategy

16.1.1 Types of Business Strategies

16.1.2 Business Strategy Frameworks

16.1.3 Barriers to Entry

16.2 Artificial Intelligence in Business Strategy

16.3 Applications of AI in Business Strategy

16.3.1 Startup Acquisition

16.3.2 Identifying Closest Competitors

16.3.3 SWOT Analysis