Category: Algorithms
How to program the K Nearest Neighbors algorithm
K Nearest Neighbors is a popular classification algorithm for supervised machine learning. It permits to divide data points into groups, defining a model that will then be able to classify an unknown data point in one group or another. The K parameter, defined during programming, allows the algorithm to classify unknown data points by examining…
How to program a Linear Regression
One of the simplest supervised machine learning tools used in data science, linear regression permits to find the best-fitting line that correlates data points in a two-dimensional space. Defining this line then enables the prediction of where other data points could be located in the space, if they have the same characteristics as the original…
Catalogue of neural networks architectures
Neural networks come in a wide range of shapes and functions, with diverse architectures and parameters for input, hidden and output nodes as well as convolutive or recurrent nodes. Regrouped in a convenient summary by Fjodor Van Veen, the most popular architectures for neural networks have been cataloged with detailed descriptions for each type of…
Programming a simple classifier with TensorFlow
TensorFlow is an open-source machine learning framework developed by Google. It relies upon Tensors (multi-dimensional arrays) which empower a wide range of API to develop machine learning applications, primarily deep neural networks. TensorFlow is commonly used in machine learning practice, so better start using it already. Thankfully the TensorFlow website provides a guide for programmers…
Programming a simple neural network
Though neural networks were considered to be of little use for a long time, the recent development of computing power and database size has proven otherwise. Since the revolution of machine learning in the last few years has been primarily driven by them, let’s dive right into the actual coding of neural nets. Before coding, it…