Book

Scala for Machine Learning

Scala is becoming the language of choice for software engineers and data scientists who analyze large data sets. This trend has been reinforced by the wide acceptance of Scala based frameworks such as Apache Spark and Kafka. As a functional language, Scala is particularly suited for extracting knowledge through supervised, unsupervised or reinforcement learning techniques. Being object-oriented, Scala ensured the construction of robust and maintainable software solutions. This book introduces the most common used machine learning models as implemented in Scala

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Difficulty Level
Intermediate
Completion Time
24h40m approx.
Language
English
Certification
Not available

About Course

Book Content

chapters 24h40m total length

1. Getting Started
2. Data pipeline
3. Data pre-processing
4. Clustering
5. Dimension reduction
6. Naïve Bayes Classifiers
7. Sequential data models
8. Monte Carlo Inference
9. Regression and Regularization
10. Multi-layer perceptron
11. Deep learning
12. Kernel models & support vector machines
13. Evolutionary computing
14. Multi-arm bandits
15. Reinforcement learning
16. Parallelism in Scala and Akka
17. Apache Spark
18. Appendix Basic concepts
19. References

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