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Shu ju fen xi yu ji qi xue xi ji chu.
数据分析与机器学习基础.
Detailed summary in vernacular field.
| Clasificación: | Libro Electrónico |
|---|---|
| Formato: | Electrónico Video |
| Idioma: | Chino Inglés |
| Publicado: |
[Place of publication not identified] :
Pearson,
2019.
|
| Edición: | [First edition]. |
| Colección: | LiveLessons (Indianapolis, Ind.)
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
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| 880 | 1 | 0 | |6 245-01/$1 |a 数据分析与机器学习基础. |
| 880 | |6 520-02/$1 |a 课程简介 几乎世界上的每一家公司都在评估自己的数字战略，并寻找利用数字化进行业务转型的机会。大数据分析和机器学习是这一战略的核心。几乎每个行业的高管、数字架构师、IT管理员和通信运营人员都需要了解数据处理和人工智能的基础知识。 在本课程中，经验丰富的两位讲师提供了有效的经验指导，带领大家探索大数据分析、监督学习、无监督学习和神经网络的基本原理。除了深入研究基本概念外，还举例介绍了不同行业的大数据和机器学习用例，并演示了数据科学家和研究人员在不同领域使用的最常见工具(如Hadoop、TensorFlow、Matlab/Octave、R和Python)。 Get技能 了解静态和实时流数据是如何收集、分析和使用的;了解机器学习和模仿人类思维的关键工具和方法: 如何收集非结构化数据，为分析和可视化做准备; 学会比较和对比各种大数据架构; 学会将有监督学习, 线性回归, 数据拟合及强化学习应用到机器学习上,以产生想要的信息结果; 将分类技术应用于机器学习，以更好地分析数据; 利用无监督学习的好处，收集到你意想不到的数据价值; 了解人工神经网络(ANNs)如何进行深度学习，并获得令人叹服的结果; 应用主成分分析(PCA)改进数据分析的管理; 了解在真实系统上实现机器学习的关键方法，以及在进行机器学习项目时必须考虑的各种事项；. | ||
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