探查数据并构建预测模型。
Get an overview of the course. Import and process data, explore data features, and train and evaluate a classification model.
Use unsupervised learning techniques to group observations based on a set of explanatory variables and discover natural patterns in a data set.
Use available classification methods to train data classification models. Make predictions and evaluate the accuracy of a predictive model.
Validate model performance. Optimize model properties. Reduce the dimensionality of a data set and simplify machine learning models.
Use supervised learning techniques to perform predictive modeling for continuous response variables.
Learn next steps and give feedback on the course.
格式:自定进度
语言:中文
了解 MATLAB 的核心功能以进行数据分析、建模和编程。
初步了解分类问题的机器学习实用方法。
学习理论和实践知识,使用真实的图像和序列数据构建深度神经网络。
MATLAB 基础知识快速入门。
了解 MATLAB 的核心功能以进行数据分析、建模和编程。
初步了解分类问题的机器学习实用方法。