K-Means is a popular unsupervised machine learning algorithm for data clustering. A typical start for flat clustering, the K-Means algorithm works by defining a number K of clusters to be extracted by the algorithm. With this K number given, the…
How to program the Support Vector Machines algorithm
Support Vector Machine is one of the most commonly used supervised machine learning algorithms for data classification. A binary classifier, the support vector machine algorithm works in vector space to sort data points by finding the best hyperplane separating them…
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…
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…
Data Science and Machine Learning for Finance
Diving deeper in data science and the actual coding of data processing functions and machine learning algorithms with Python, this series of tutorial gives us a great taste of what can be done in finance and stock trading. Through a…