By Jeff Hale, Data Scientist Focused on Machine Learning - CoFounder and COO at E-commerce Firms.

Toward the end of my PhD analysis, I’ve started leaning on purrr more and more to get analysis done on small multiples quickly and safely. Where before I might have used nested loops and potentially missed a lot of problems, I now split data frames out, build statistical models, extract model parameters and print plots all in one workflow.

Python continues to lead the way when it comes to Machine Learning, AI, Deep Learning and Data Science tasks. According to builtwith.com, 45% of technology companies prefer to use Python for implementing AI and Machine Learning.

The International Data Corporation (IDC) estimates that by 2021, enterprise spending on artificial intelligence (AI) and machine learning will more than triple that of 2017. However, companies looking to use AI encounter challenges such as a lack of clear implementation best practices along with fierce competition for data science resources.

Submit! If you haven’t made a Kaggle competition submission, this is a great moment to jump in. Here’s a rundown of current competitions, trending Kernels, and tips from winners.​

Introduction Writing appealing interactive web applications – one of STATWORX’s many competences – is an ease with R shiny. Just a few lines of code in one R script create the whole logic you need to let the whole magic of shiny happen. It is so simple that you can make a hello world app in a heartbeat, like so.

The International Data Corporation (IDC) estimates that by 2021, enterprise spending on artificial intelligence (AI) and machine learning will more than triple that of 2017. However, companies looking to use AI encounter challenges such as a lack of clear implementation best practices along with fierce competition for data science resources.

What is Machine Learning?