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The course ‘Machine Learning com Python’ on Udemy offers an extensive introduction to various machine learning algorithms using Python, catering primarily to beginners but also covering intermediate and advanced techniques. The course is well-structured, beginning with fundamental Python skills in Google Colaboratory, moving through essential statistical concepts, and then diving into real-world applications of supervised, unsupervised, and reinforcement learning. It covers a broad spectrum of algorithms including XGBoost, Catboost, LightGBM, Naive Bayes, Random Forest, Decision Trees, SVM, KNN, Artificial Neural Networks, and more, ensuring students gain practical experience with modern and widely-used tools. What sets this course apart is its focus on applied learning — from data acquisition to preprocessing and algorithm implementation, all resources like slides, scripts, and datasets are provided. The instructor emphasizes clear, step-by-step explanations, making complex topics accessible without delving into heavy mathematical detail. Additionally, the course is dynamic; updates and new content are continually added based on student feedback, keeping it current and relevant. Whether you’re just starting out or looking to strengthen your machine learning skills, this course is a valuable resource that demystifies the world of machine learning with practical, easy-to-follow lessons.
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