{"id":13214,"date":"2026-08-10T10:56:12","date_gmt":"2026-08-10T10:56:12","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/udemy-generative-ai-and-machine-learning-with-python-2025-3\/"},"modified":"2026-08-10T10:56:12","modified_gmt":"2026-08-10T10:56:12","slug":"udemy-generative-ai-and-machine-learning-with-python-2025-3","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/udemy-generative-ai-and-machine-learning-with-python-2025-3\/","title":{"rendered":"Udemy \u2013 Generative AI and Machine Learning with Python 2025-3"},"content":{"rendered":"
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Description<\/span><\/h2>\n

Generative AI and Machine Learning with Python. This course provides a structured and thorough review of the field from fundamentals to advanced. The course begins by teaching the principles of supervised, unsupervised, and reinforcement learning, and then moves on to practical concepts such as data preprocessing, evaluation criteria, and basic algorithms including linear regression, logistic regression, decision trees, and random forests. The unsupervised learning section covers topics such as K-means clustering and principal component analysis for data dimensionality reduction. The focus then shifts to deep learning with artificial neural networks, convolutional neural networks, and multilayer perceivers using the Keras library. The final section of the course explores advanced generative AI technologies such as transformer attention mechanisms, generative adversarial networks, variational autoencoders, recurrent neural networks, and gated recurrent units. Combining hands-on Python coding labs, rigorous evaluation of models with various metrics and confusion matrices, and regular quizzes after each module, this course provides a comprehensive understanding for learners from beginner to advanced levels.<\/span><\/p>\n

What you will learn<\/span><\/h3>\n