Machine Learning with Scikit-Learn
In the video, data scientist Michael Galarnyk delves into the practical application of scikit-learn, a popular Python library for machine learning.The course focused on supervised and unsupervised machine learning techniques. My role involved actively engaging with the tutorial, grasping the functionalities of scikit-learn’s API, and implementing various algorithms like linear regression, logistic regression, decision trees, random forests, K-means clustering, and PCA. Through this comprehensive overview, I gained a nuanced understanding of the strengths and weaknesses of each algorithm, learned how to create scikit-learn pipelines for cleaner code, and enhanced my ability to develop more efficient machine learning models.