Predictive analytics: Data Mining, Machine Learning, and Data Science for Practitioners

• Naive Bayes
• Nearest Neighbor
• Similarity Measure: The Distance Metric
• Artificial Neural Networks
• Support Vector Machines
• Linear Regression
• Logistic Regression
• Time-Series Forecasting
• Summary
• References

4 LiveLab in this lesson — see the labs panel →

• Model Ensembles
• Bias–Variance Trade-off in Predictive Analytics
• Imbalanced Data Problems in Predictive Analytics
• Explainability of Machine Learning Models for Predictive Analytics
• Summary
• References

1 LiveLab in this lesson — see the labs panel →

• Natural Language Processing
• Text Mining Applications
• The Text Mining Process
• Text Mining Tools
• Topic Modeling
• Sentiment Analysis
• Summary
• References

2 LiveLab in this lesson — see the labs panel →

• Where Does Big Data Come From?
• The Vs That Define Big Data
• Fundamental Concepts of Big Data
• The Business Problems That Big Data Analytics Addresses
• Big Data Technologies
• Data Scientists
• Big Data and Stream Analytics
• Data Stream Mining
• Summary
• References

• Introduction to Deep Learning
• Basics of “Shallow” Neural Networks
• Elements of an Artificial Neural Network
• Deep Neural Networks
• Convolutional Neural Networks
• Recurrent Networks and Long Short-Term Memory Networks
• Computer Frameworks for Implementation of Deep Learning
• Cognitive Computing
• Summary
• References

• Project Constraints: Time and Money
• The Learning Curve
• The KNIME Community
• Correctness and Flexibility
• Extensive Coverage of Data Science Techniques
• Data Science in the Enterprise
• Summary and Conclusions
• Acknowledgment

• Introduction to Predictive Analytics
• Introduction to Predictive Analytics and Data Mining
• The Data Mining Process
• Data and Methods in Data Mining
• Data Mining Algorithms
• Text Analytics and Text Mining
• Big Data Analytics
• Predictive Analytics Best Practices
• Summary

• Running Python Statements
• Jupyter Notebooks
• Google Colab
• Summary
• Questions

• Basic Types in Python
• Performing Basic Math Operations
• Using Classes and Objects with Dot Notation
• Summary
• Questions

2 LiveLab in this lesson — see the labs panel →

• Defining Functions
• Scope in Functions
• Decorators
• Anonymous Functions
• Summary
• Questions

2 LiveLab in this lesson — see the labs panel →

• Installing and Importing NumPy
• Creating Arrays
• Indexing and Slicing
• Element-by-Element Operations
• Filtering Values
• Views Versus Copies
• Some Array Methods
• Broadcasting
• NumPy Math
• Summary
• Questions

3 LiveLab in this lesson — see the labs panel →

• Popular Machine Learning Libraries
• How Machine Learning Works
• Learning More About Scikit-learn
• Summary
• Questions

1 LiveLab in this lesson — see the labs panel →