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Advanced Machine Learning with scikit-learn Training Video

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Advanced Machine Learning with scikit-learn Training Video

SKU: 02193 | .MP4, AVC, 1000 kbps, 1280x720 | English, AAC, 64 kbps, 2 Ch | 4 hours | 766 MB

Instructor: Andreas C. Mueller

In this Advanced Machine Learning with scikit-learn training course, expert author Andreas Mueller will teach you how to choose and evaluate machine learning models. This course is designed for users that already have experience with Python. 

You will start by learning about model complexity, overfitting and underfitting. From there, Andreas will teach you about pipelines, advanced metrics and imbalanced classes, and model selection for unsupervised learning. This video tutorial also covers dealing with categorical variables, dictionaries, and incomplete data, and how to handle text data. Finally, you will learn about out of core learning, including the sci-learn interface for out of core learning and kernel approximations for large-scale non-linear classification.

Once you have completed this computer based training course, you will have learned everything you need to know to be able to choose and evaluate machine learning models. Working files are included, allowing you to follow along with the author throughout the lessons.

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  1. 高级机器学习与scikit学习培训视频 编号:02193 导师:安德烈亚斯穆勒C. 在这种先进的机器学习与scikit学习培训班,专家撰文安德烈亚斯穆勒将教你如何选择和评估机器学习模型。本课程是专为已经有使用Python体验。 您将通过学习模型的复杂性,过度拟合和欠拟合开始。从那里,安德烈亚斯将教你管线,先进的指标和不平衡类,模型选择的无监督学习。本视频教程还介绍了处理分类变量,字典和不完整的数据,以及如何处理文本数据。最后,您将了解了核心的学习,包括了核心学习和内核近似为大规模非线性分类SCI学习的界面。 一旦你完成了这个基于计算机的培训课程中,你会学到你需要知道的能够选择和评估机器学习模型的一切。工作文件都包括在内,让您在整个课撰文进行操作。
    stxpnet10个月前 (05-24)