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Classification Using Tree Based Models

Classification Using Tree Based Models
Classification Using Tree Based Models
Duration: 1h 56m | Video: h264, yuv420p 1280x720 | Audio: aac, 44100 Hz, 2 ch | 239 MB
Genre: eLearning | Language: English | Project Files

Machine Learning can sound very complicated, but anyone with a will to learn can successfully apply it, if they approach it from first principles. This course, Classification Using Tree Based Models, covers a specific class of Machine Learning problems - classification problems and how to solve these problems using Tree based models. First, you'll learn about building and visualizing decision trees as well as recognizing the serious problem of overfitting and its causes. Next, you'll learn about using ensemble learning to overcome overfitting. Finally, you'll explore 2 specific ensemble learning techniques - Random Forests and Gradient boosted trees By the end of this course, you'll be able to recognize opportunities where you can use Tree based models to solve classification problems and measure how well your solution is doing.

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