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This guide is the third and final part of three guides about Support Vector Machines (SVMs). In this guide, we will keep working with the forged bank notes use case, have a quick recap about the general idea behind SVMs, understand what is the kernel trick, and implement different types...
Cássia Sampaio
This guide is the second part of three guides about Support Vector Machines (SVMs). In this guide, we will keep working on the forged bank notes use case, understand what SVM parameters are already being set by Scikit-Learn, what are C and Gamma hyperparameters, and how to tune them using...
This guide is the first part of three guides about Support Vector Machines (SVMs). In this series, we will work on a forged bank notes use case, learn about the simple SVM, then about SVM hyperparameters and, finally, learn a concept called the kernel trick and explore other types of...
You are working in a consulting company as a data scientist. The project you were currently assigned to has data from students who have recently finished courses about finances. The financial company that conducts the courses wants to understand if there are common factors that influence students to purchase the...
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Tree-based models have become a popular choice for Machine Learning, not only due to their results, and the need for fewer transformations when working with data (due to robustness to input and scale invariance), but also because there is a way to take a peek inside of them to see...
Decision trees are widely used in machine learning problems. We'll assume you are already familiar with the concept of decision trees and you've just trained your tree based algorithm! Advice: If not, you can read our in-depth guide on "Decision Trees in Python with Scikit-Learn guide". Now, it...
The Random Forest algorithm is one of the most flexible, powerful and widely-used algorithms for classification and regression, built as an ensemble of Decision Trees. If you aren't familiar with these - no worries, we'll cover all of these concepts. In this in-depth hands-on guide, we'll build an intuition on...
The Random Forest algorithm is a tree-based supervised learning algorithm that uses an ensemble of predictions of many decision trees, either to classify a data point or determine its approximate value. This means it can either be used for classification or regression. When applied for classification, the class of the...
Sometimes confused with linear regression by novices - due to sharing the term regression - logistic regression is far different from linear regression. While linear regression predicts values such as 2, 2.45, 6.77 or continuous values, making it a regression algorithm, logistic regression predicts values such as 0...
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