If you run an e-commerce website a classical problem is to rank your product offering in the search page in a way that maximises the probability of your items being sold. For example if you are selling shoes you would like the first pair of shoes in the search result page to be the one … Learning to rank with Python scikit-learn
Everyone loves isolation. Makes our life easier and our systems much more robust. Isolating Jupyter notebooks makes no exception. Maybe you want to try some cutting edge scientific library, or more simply your latest project dependencies are not compatible with your current system setup. Whatever is your situation, follow me in this simple tutorial on how to … Create isolated Jupyter ipython kernels with pyenv and virtualenv
Cross validation is an essential tool in statistical learning to estimate the accuracy of your algorithm. Despite its great power it also exposes some fundamental risk when done wrong which may terribly bias your accuracy estimate. In this blog post I’ll demonstrate – using the Python scikit-learn framework – how to avoid the biggest and … Cross Validation done wrong
Both R and Python are incredibly good tools to manipulate your data and their integration is becoming increasingly important. The latest tool for data manipulation in R is Dplyr whilst Python relies on Pandas. In this blog post I’ll show you the fundamental primitives to manipulate your dataframes using both libraries highlighting their major advantages … Data manipulation primitives in R and Python