Learning Path: Scala: Efficient Data Analysis with Scala

Course details

Data analysis is a process for inspecting, consolidating, transforming, and making sense of data in a way that guides the decision-making process. Scala has emerged as an important tool for efficiently performing various data analysis tasks. So, if you're interested to load raw datasets with Spark, and perform exploratory data analysis on those via plotting Scala libraries, then go for this Learning Path.

Packt's Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it.

The highlights of this Learning Path are:

• Learn data processing, analytics, and visualization in Scala
• Integrate deep learning with Spark
• Explore Deeplearning4j and plotting with Bokeh

Let's take a quick look at your learning journey. This Learning Path will help you leverage popular Scala libraries and tools and perform core data analysis tasks with ease. You will see how to load raw data sets with Spark and perform exploratory data analysis on them via plotting. You will then learn what Spark has to offer when it comes to transforming data sets and how you can build a statistical model of a data set with Spark. Moving ahead, you will be introduced to Deeplearning4j and start with tasks such as integrating with Spark and linear regression with deep learning. You will make use of popular Scala libraries such as Breeze and Bokeh to plot your data.

By the end of this Learning Path, you will be able to analyze and plot your data efficiently.

Meet Your Expert:

We have combined the best works of the following esteemed author to ensure that your learning journey is smooth: 

Anatolii Kmetiuk has been working with Scala-based technologies for four years. He has experience in deep learning models for text processing. He is interested in category theory and type-level programming in Scala. Another field of interest is chaos and complexity theory and artificial life, and ways to implement them in programming languages.