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最新課程列表

• ?此課程重點(diǎn)介紹 MATLAB 中使用 Statistics Toolbox , Machine Learning Toolbox? 和

  Deep Learning Toolbox? 功能的數(shù)據(jù)分析和機(jī)器學(xué)習(xí)技術(shù)。本課程
  演示如何通過非監(jiān)督學(xué)習(xí)發(fā)現(xiàn)大數(shù)據(jù)集的特點(diǎn)，以及通過監(jiān)督學(xué)
  習(xí)建立預(yù)測模型。課程中的示例和練習(xí)強(qiáng)調(diào)用于呈現(xiàn)和評(píng)估結(jié)果
  的技巧。內(nèi)容包括：

  • 組織和預(yù)處理數(shù)據(jù)
  • 聚類數(shù)據(jù)
  • 創(chuàng)建分類模型
  • 評(píng)估和改善模型
  • 化簡數(shù)據(jù)集
  • 改善模型性能??
  • 詳細(xì)課程提綱：

  • 課程要求

    MATLAB 基礎(chǔ)

    Importing and Organizing Data	Objective:?Bring data into MATLAB and organize it for analysis, including normalizing data and removing observations with missing values. ·?Data types ·?Tables ·?Categorical data ·?Data preparation
    Finding Natural Patterns in Data	Objective:?Use unsupervised learning techniques to group observations based on a set of explanatory variables and discover natural patterns in a data set. ·?Unsupervised learning ·?Clustering methods ·?Cluster evaluation and interpretation
    Building Classification Models	Objective:?Use supervised learning techniques to perform predictive modeling for classification problems. Evaluate the accuracy of a predictive model. ·?Supervised learning ·?Training and validation ·?Classification methods

    ?

    Improving Predictive Models	Objective:?Reduce the dimensionality of a data set. Improve and simplify machine learning models. ·?Cross validation ·?Hyperparameter optimization ·?Feature transformation ·?Feature selection ·?Ensemble learning
    Building Regression Models	Objective:?Use supervised learning techniques to perform predictive modeling for continuous response variables. ·?Parametric regression methods ·?Nonparametric regression methods ·?Evaluation of regression models
    Creating Neural Networks	Objective:?Create and train neural networks for clustering and predictive modeling. Adjust network architecture to improve performance. ·?Clustering with Self-Organizing Maps ·?Classification with feed-forward networks ·?Regression with feed-forward networks

    ?

  
  
  

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