Adding internal links to articles helps reduce bounce rate by promoting related content site visitors may find interesting, but it also has a powerful impact upon search engine optimisation or...
Tokenization is a data science technique that breaks up the words in a sentence into a comma separated list of distinct words or values. It’s a crucial first step in...
In ecommerce, you’ll typically be given a revenue target your site needs to hit every month. In my experience, these revenue targets are often proposed by finance directors, CEOs, or...
Naive Bayes classifiers are commonly used for machine learning text classification problems, such as predicting the sentiment of a tweet, identifying the language of a piece of text, or categorising...
When training a machine learning model you will split your dataset in two, with one portion of the data used to train the model, and the other portion (usually 20-30%)...
The random forest model or random decision forest model is a supervised machine learning algorithm that can be used for classification or regression problems. It’s what’s known as an ensemble...
The Decision Tree or DT is one of the most well known and most widely used supervised machine learning algorithms and can be applied to both regression and classification. As...
When working with Python lists you’ll often encounter times when you need to remove duplicate values present in a single list, remove duplicates found in multiple lists, or identify the...
When working with customer data or upon time series data science projects, you’ll often find the need to calculate the difference between two dates in your MySQL queries. The MySQL...
