Once you create a data frame with R, you may need to load it to a relational database for data persistence. You might have a data transformation batch job written in R and want to load database in a certain frequency. Here, I created a function to load data into …

Once you finish training the model and are happy with it, you may need to consider saving the model. Otherwise, you will loose the model once you close the session. The model you create in R session is not persistent, only existing in the memory temporarily. Most of the time, …

Writing code to do machine learning is easy. What makes it difficult is the optimisation. By large, there are two ways to optimise your model. Feature selection & transformation Model parameter optimisation Both are hard-core topics and neither can be covered in this post. Feature selection and transformation often require …

I love dissecting and analysing my favourite books by reading them again and again, discussing them with my like-minded friends, getting to know the authors and reading other people’s writings about them. My obsession with books lead me to thinking, how can I visualise them in interesting ways? Making Word …

Making a word cloud is fun and easy. It is a way of looking at text data and gain a different perspective. For example, if you have a bunch of customer feedback about your product, you can quickly create a word cloud to get some ideas. When I work with …

How To Customise ShinyApp With Bootstrap CSS, Javascript And Plotly What is the easiest way to make a data science product? My answer is to use Shiny. You can code both front-end and server-side in R to create beautiful interactive web applications. You don’t even need to know any HTML. …

In the previous post, we discussed how to ingest data from Liveperson with Python. In this post, I want to use R to make the same API call and create an aggregated table instead of preparing data for ingestion. The code is based on the example here. For further information …