The ability to apply machine learning techniques to large datasets is becoming a highly sought-after skill in the world of technology. Scala can help you deliver key insights into your data—its unique capabilities as a language let you build sophisticated algorithms and statistical models. For this reason, machine learning and Scala fit together perfectly and knowledge of both would be beneficial for anyone entering the data science field.
The course starts with a general introduction to the Scala programming language. From there, you’ll be introduced to several practical machine learning algorithms from the areas of exploratory data analysis. You’ll look at supervised learning machine learning models for prediction and classification tasks, and unsupervised learning techniques such as clustering and dimensionality reduction and neural networks.
By the end, you will be comfortable applying machine learning algorithms to solve real-world problems using Scala.
Write Scala code implementing neural network models for prediction and clustering
Plot and analyze the structure of datasets with exploratory data analysis techniques using Scala
Use new and popular Scala frameworks such as Akka and Spark to implement machine learning algorithms and Scala libraries such as Breeze for numerical computing and plotting
Get to grips with the most popular machine learning algorithms used in the areas of regression, classification, clustering, dimensionality reduction, and neural networks
Use the power of MLlib libraries to implement machine learning with Spark
Work with the k-means algorithm and implement it in Scala with the real datasets
Get to know what dimensionality reduction is and explore the theory behind how the PCA algorithm works
Analyze and implement linear regression and GLMs in Scala and run them on real datasets
Use the Naive bayes algorithms and its methods to predict the probability of different classes based on various attributes
Prior knowledge of one of the JVM languages and basic knowledge in math and statistics is required.
Who is this course intended for?
This course is for those who wish to make sense of their complex data and get hidden insights from it. If you want to build smarter, more accurate Scala applications, this course is for you.