Bag of Words
Wikipedia says: “The bag-of-words model is a model of text which uses a representation of text that is […]
Machine Learning
Decision Tree – Only Six Rows
This is a very simple example of building a decision tree model on a very small dataset that […]
Decision Tree Workflow
Are you working in Python? Do you want to build a decision tree? Let’s work though this workflow […]
Decision Trees and Random Forests
A random forest is a collection of decision trees whose results are aggregated into one final result. Their […]
Decision Tree 4 Rows
Let’s learn about decision trees with a dataset that has only four rows of generic data, and two […]
Naive Bayes Python Example
Here is an example of Naive Bayes. I created a project using Jupyter Notebook that I called Naive […]
Confusion Matrix
What is a confusion matrix? a confusion matrix is a graphic that shows you your models true and […]
Evaluate Supervised Categorical Models
In the forth of four stages of the PACE Framework of Google, lies the Evaluate stage. The first […]
Class Imbalance in a Dataset
When a dataset has a predictor variable that contains more instances of one outcome than another, we have […]
K-Means Algorithm
K-means is an unsupervised partitioning algorithm. It’s used to organize unlabeled data into groups or clusters. What does […]
Hyperparameter Tuning
A popular and widely used technique to improve model performance after creation is known as hyperparameter tuning. Hyperparameters […]
Decision Tree Python Algorithm
Here’s a brief summary of what we need to do in Python. I’m thinking of Jupyter Notebook. There’s […]