After some exploration and analysis of the data it’s time to create a predictive model. In this episode you’ll discover several new chart types, learn how to evaluate the correlation between variables, how to create a simple linear model, and how to evaluate the fitness of the model.
With the knowledge of transducers under your belt, it’s time to start analyzing some data. This episode provides a first introduction to the Kixi.stats statistical toolkit, by analyzing a data set and its distribution, with the goal of creating a predictive model through linear regression.
Clojure allows processing data in a way that is composable, reusable, and performs well, all through the power of Transducers. Episode 38 provided a general overview of what’s in the box, the transducers and transducing contexts provided by clojure.core. This episode digs deeper into the internals of transducers and reducing functions, and looks at some powerful libraries for real-world data processing and statistics.
React’s component based approach means you don’t have to reinvent the wheel, there are literally thousands of building blocks freely available.
When using React components from Reagent there are a few things to watch out for, this episode will show you how to use some popular React components from Reagent, and point out useful constructs and patterns.
You’ll also get to see some of the new
cljs.main feature that landed in