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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/big-data-machine-learning
课程评论：没有评论
课程名称：大数据机器学习 概述：您是否希望理解收集的大量数据？是否需要在您的流程中融入数据驱动的决策？本课程提供了机器学习技术的概述，帮助您探索、分析和利用数据。您将学习可以创建机器学习模型的工具和算法，这些模型能够从数据中学习，并将这些模型扩展到大数据问题。 课程结束时，您将能够： • 设计利用数据的方法，掌握机器学习过程中的各个步骤。 • 应用机器学习技术探索和准备建模数据。 • 确定机器学习问题的类型，从而应用适当的技术。 • 使用广泛可用的开源工具构建能够从数据中学习的模型。 • 使用Spark上的可扩展机器学习算法分析大数据问题。 软件要求： Cloudera VM，KNIME，Spark 课程大纲： 第一部分：大数据机器学习导论 第二部分：数据准备 第三部分：分类 第四部分：机器学习模型评估 第五部分：回归、聚类分析和关联分析
Part: 1
Title:Introduction to Machine Learning with Big Data
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Part: 2
Title:Data Preparation
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Part: 3
Title:Classification
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Part: 4
Title:Evaluation of Machine Learning Models
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Part: 5
Title:Regression, Cluster Analysis, and Association Analysis
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Want to make sense of the volumes of data you have collected? Need to incorporate data-driven decisions into your process? This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up to big data problems. At the end of the course, you will be able to: • Design an approach to leverage data using the steps in the machine learning process. • Apply machine learning techniques to explore and prepare data for modeling. • Identify the type of machine learning problem in order to apply the appropriate set of techniques. • Construct models that learn from data using widely available open source tools. • Analyze big data problems using scalable machine learning algorithms on Spark. Software Requirements: Cloudera VM, KNIME, Spark
