Artificial Intelligence in Business Management

✍ Scribed by Teik Toe Teoh , Yu Jin Goh

• Publisher: Springer International Publishing
• Year: 2023
• Tongue: English
• Leaves: 385
• Category: Library

✦ Table of Contents

Preface
Acknowledgments
Contents
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
Exercises
References
Index