

Machine Learning Courses
Master Python fundamentals in this hands-on course designed for beginners. Learn essential concepts like data types, control structures, functions, modules, and data structures through interactive labs and practical challenges. Perfect for those starting their Python programming journey.
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Supervised learning. If you are hearing or reading this term for the first time, then it may be completely unclear what it means. Don't worry. In this lab, you will get a comprehensive understanding of supervised learning; and, in the next chapter of the experiment, you will learn to use supervised learning to complete data prediction.
Completed 0 of 7 Labs
During this course, we will continue to learn another important application in supervised learning - solving classification problems. In the following lessons, you will be exposed to: logistic regression, K-nearest neighbor algorithm, naive Bayes, support vector machine, perceptron and artificial neural network, decision tree and random forest, and bagging and boosting methods. The course will start with the principle of each of these methods. You are supposed to fully understand the implementat
Completed 0 of 10 Labs
In this course, you will fully understand unsupervised learning and learn to use unsupervised learning to perform data clustering.
Completed 0 of 9 Labs
In this course, you will learn the basic concepts of deep learning, including the basic principles of neural networks, the basic principles of TensorFlow, Keras and PyTorch, and the basic principles of linear regression, logistic regression, and multi-layer neural networks. You will also learn how to use TensorFlow, Keras and PyTorch to build a linear regression model, a logistic regression model, and a multi-layer neural network model.
Completed 0 of 7 Labs
This comprehensive course covers the fundamental concepts and practical techniques of Scikit-learn, the essential machine learning library in Python. Learn to build, train, and evaluate machine learning models using various algorithms and preprocessing techniques.
Completed 0 of 7 Labs
In this course, you will learn the basic concepts and syntax of TensorFlow 2, and how to use TensorFlow 2 to implement deep learning algorithms.
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