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Statistical Methods and Applied Mathematics in Data Science


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Statistical Methods and Applied Mathematics in Data Science
Statistical Methods and Applied Mathematics in Data Science
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 2.5 Hours | 623 MB
Genre: eLearning | Language: English

Machine learning and data analysis are the center of attraction for many engineers and scientists. The reason is quite obvious: its vast application in numerous fields and booming career options. And Python is one of the leading open source platforms for data science and numerical computing. IPython, and its associated Jupyter Notebook, provide Python with efficient interfaces to for data analysis and interactive visualization, and they constitute an ideal gateway to the platform. If you are among those seeking to enhance their capabilities in machine learning, then this course is the right choice.

Statistical Methods and Applied Mathematics in Data Science provides many easy-to-follow, ready-to-use, and focused recipes for data analysis and scientific computing. This course tackles data science, statistics, machine learning, signal and image processing, dynamical systems, and pure and applied mathematics. You will apply state-of-the-art methods to various real-world examples, illustrating topics in applied mathematics, scientific modeling, and machine learning. In short, you will be well versed with the standard methods in data science and mathematical modeling.

The code bundle for the video course is available at: http://github.com/PacktPublishing/Statistical-Methods–-Applied-Mathematics-in-Data-Science.

Statistical Methods and Applied Mathematics in Data Science

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  1. 对许多工程师和科学家来说,机器学习和数据分析是他们的最爱。原因是显而易见的:它们在众多领域的广泛应用同时也是红火的职业选择。Python是领先的数据科学和数值计算开源平台之一。IPython及其相关联的Jupyter笔记本为Python提供了高效的数据分析和交互式可视化界面,并且它们构成了平台的理想网关。如果你是那些寻求提高机器学习能力的人之一,那么这门课程是正确的选择。 数据科学中的统计方法和应用数学为数据分析和科学计算提供了许多易于遵循、易于使用和重点突出的方法。这门课程涉及数据科学、统计学、机器学习、信号和图像处理、动力系统以及纯数学和应用数学。你将把最新的方法应用到各种现实世界的例子中,展示应用数学、科学建模和机器学习的主题。简而言之,你将精通数据科学和数学建模的标准方法。
    sunsource(特殊组-翻译)3个月前 (07-30)