Principles of Machine Learning: R Edition. MPP

Este curso pertenece al Microsoft Professional Program for Data Science

 

Índice

Before You Start
  • Start Here
Module 1: Introduction to Machine Learning
  • High Level Data Science Process
  • Overview of Machine Learning
  • Lab: Lab 1 Introduction to Machine Learning

Module 2: Exploring Data

  • Exploratory Data Analysis for Regression 
  • Exploratory Data Analysis for Classification
  • Lab: Visualizing Data for Regression

    Module 3: Data Preparation and Cleaning

    • Data Preparation and Cleaning
    • Feature Engineering
    • Lab: Data Preparation

      Module 4:  Getting Started with Supervised Learning

      • Regression
      • Classification
      • Lab: Introduction to Regression

        Module 5: Improving Model Performance

        • Principles of Model Improvement
        • Techniques for Improving Models
        • Dimensionality Reduction
        • Lab: Bias-Variance Trade-Off

        Module 6: Machine Learning Algorithms

        • Introduction to Decision Trees
        • Ensemble Methods
        • Neural Networks
        • Support Vector Machines (SVMs)
        • Bayes Theorem
        • Lab: Bagging

        Module 7: Unsupervised Learning

        • Clustering
        • Lab: Introduction to Unsupervised Learning

        Final Exam and Survey

        • Final Challenge
        • Congratulations

        Get Microsoft Course Completion Certificate

        • Instructions

        Soporte

        Curso con soporte individualizado según se indica en https://nanfor.com/pages/soporte-2-0 

         

        * Todas las tarifas son bonificables menos el examen solo.

          €295.00