Semestre 2

This machine learning course takes you on an immersive journey into the realm of predictive algorithms and intelligent data analysis. We'll explore various supervised learning techniques, starting with fundamental algorithms like KNN, Decision Trees, and Naïve Bayes, commonly used for classification tasks such as spam detection and sentiment analysis. You'll gain proficiency in more complex models like Support Vector Machines for their precision in high-dimensional spaces and the Perceptron for its role in laying the groundwork for neural networks.

We'll dive deep into neural networks, unpacking the principles that allow these powerful models to approximate almost any function and learn from data. You'll learn how to train these networks, understand activation functions, and implement forward and backpropagation techniques. By the end of this course, you'll have a robust understanding of the key machine learning techniques and be equipped to apply them to a variety of real-world challenges.