What are missing values in machine learning? Missing values in a dataset indicate the absence of observations. The danger of missing values Why are missing values a problem for our job? Missing values bring mainly 2 problems: Types of missing…
What are categorical features – recap In categorical features, measurements can assimilate a number of limited and fixed values, called “categories“. There are 2 types of categorical features: Why can’t most ML models deal with categorical values? Artificial intelligence models…
What is feature engineering? Feature engineering is selecting, extracting, and transforming features from raw data to create a new dataset useful for building predictive models. This new dataset is compatible with our algorithm and provides the model with more valuable…
Types of classification outputs Positive and negative outputs In a classification problem, there are 2 types of categories, positive and negative. Positive categories are labels with a particular characteristic that we are interested in. All the other categories are negative.…
What is a validation metric? A validation metric is a formula we use during model validation to confront the model predictions with the actual output values. The choice of a validation metric depends on the type of the problem. Validation…
What is model validation? Model validation is the step that comes after training. During model validation, we evaluate the accuracy of our model by seeing how it performs with data he hasn’t been trained on. This way we verify that…
In machine learning, we can identify data as a set of observations or measurements, called dataset, used to train and test a machine learning model. Data are crucial because artificial intelligence is built on them, and their quantity and quality…
Bias and variance are 2 fundamental metrics to describe a model’s ability to resolve a problem. Let’s say we have a dataset like this one. We want to represent the relationships between the x and y to predict new values.…
In this article, I’ll show you how to program linear regression from scratch in Python using ONLY MATH. Let’s get started. Why is coding linear regression from scratch useful? When I study a new machine learning model, I always get…
What linear regression is Linear regression is a supervised machine-learning algorithm that fits a straight line to the input data to represent the relationship between x and y. Linear regression structure Suppose we have a dataset that contains two columns,…