In the last entry for this series, we created a Random Forest model to try and predict which passengers survived their trip on the Titanic. Without any customisation of the Random Forest, we were able to achieve an accuracy of 0.75119, not as good as …
Last time we ran through the exploratory data analysis to Pre-processing The first step of creating models is the pre-processing of your data. Cleaning the data up to remove nulls, applying any scaling or normalising you need and potentially aggregating the raw data you are …
The Journey Begins For any budding Data Scientist to build their data science chops and reputation, they need to develop lots of models in different applications. One of the best resources to do that and see how well you are doing compared to other people …
Once you start getting into data science one of the biggest challenges you face, and where much of your time is spent, is getting data into a tidy and usable state. I came across an blog post (by Jean-Nicolas Hould) recently which applied the process …