Course Description
Machine learning algorithms types,
in this course we will learn about the types of machine learning algorithms, a cornerstone of AI development. Starting with an introduction to Supervised Learning, you will explore algorithms like linear regression, logistic regression, decision trees, and support vector machines, which rely on labeled data to predict outcomes. Next, we delve into Unsupervised Learning, covering clustering techniques like K-means and dimensionality reduction methods like PCA, used for finding hidden patterns in unlabeled data. We'll also discuss Reinforcement Learning, where agents learn through rewards and penalties, and Semi-Supervised Learning, a hybrid approach. Additionally, you’ll gain insights into Ensemble Learning methods like boosting and bagging, and their applications in complex problems. By the end, you'll understand the strengths and use cases of each type, preparing you to choose the right algorithm for any data-driven challenge. TutorialsPoint
