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  Machine Learning Fundamentals with Scala and Apache Spark培訓

Introduction to Applied Machine Learning
Statistical learning vs. Machine learning
Iteration and evaluation
Bias-Variance trade-off
Machine Learning with Scala
Choice of libraries
Add-on tools
Regression
Linear regression
Generalizations and Nonlinearity
Exercises
Classification
Bayesian refresher
Naive Bayes
Logistic regression
K-Nearest neighbors
Exercises
Cross-validation and Resampling
Cross-validation approaches
Bootstrap
Exercises
Unsupervised Learning
K-means clustering
Examples
Challenges of unsupervised learning and beyond K-means