Predictive Modeling and Machine Learning with MATLAB

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课程主页: https://www.coursera.org/archive/predictive-modeling-machine-learning

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In this course, you will build on the skills learned in Exploratory Data Analysis with MATLAB and Data Processing and Feature Engineering with MATLAB to increase your ability to harness the power of MATLAB to analyze data relevant to the work you do. These skills are valuable for those who have domain knowledge and some exposure to computational tools, but no programming background. To be successful in this course, you should have some background in basic statistics (histograms, averages, standard deviation, curve fitting, interpolation) and have completed courses 1 through 2 of this specialization. By the end of this course, you will use MATLAB to identify the best machine learning model for obtaining answers from your data. You will prepare your data, train a predictive model, evaluate and improve your model, and understand how to get the most out of your models.

使用MATLAB进行预测性建模和机器学习:在本课程中,您将学习使用MATLAB探索性数据分析以及使用MATLAB进行数据处理和特征工程学到的技能,从而提高利用MATLAB的能力分析与工作相关的数据的能力你做。 这些技能对于那些具有领域知识并且对计算工具有所了解但没有编程背景的人来说非常有价值。为使本课程取得成功,您应该具有基本统计知识的背景知识(直方图,平均值,标准差,曲线拟合,插值),并已完成本专业的课程1至2。 在本课程结束时,您将使用MATLAB识别最佳机器学习模型,以便从数据中获取答案。您将准备数据,训练预测模型,评估和改进模型,并了解如何充分利用模型。

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