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Doing Data Science with Python

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Doing Data Science with Python
Doing Data Science with Python
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 6.5 Hours | 925 MB
Genre: eLearning | Language: English

This course shows you how to work on an end-to-end data science project including processing data, building & evaluating machine learning model, and exposing the model as an API in a standardized approach using various Python libraries.

Do you want to become a Data Scientist? If so, this course will equip you with concepts and tools that can bring you to speed and you can utilize the skills acquired in this course to work on any data science project in a standardized approach. This course, Doing Data Science with Python, follows a pragmatic approach to tackle end-to-end data science project cycle right from extracting data from different types of sources to exposing your machine learning model as API endpoints that can be consumed in a real-world data solution. This course will not only help you to understand various data science related concepts, but also help you to implement the concepts in an industry standard approach by utilizing Python and related libraries. First, you will be introduced to the various stages of a typical data science project cycle and a standardized project template to work on any data science project. Then, you will learn to use various standard libraries in the Python ecosystem such as Pandas, NumPy, Matplotlib, Scikit-Learn, Pickle, Flask to tackle different stages of a data science project such as extracting data, cleaning and processing data, building and evaluating machine learning model. Finally you'll dive into exposing the machine learning model as APIs. You will also go through a case study that will encompass the whole course to learn end-to-end execution of a data science project. By the end of this course, you will have a solid foundation to handle any data science project and have the knowledge to apply various Python libraries to create your own data science solutions.

Doing Data Science with Python

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  1. 数据科学中的Python 本教程将会为你带来如何处理终端对终端的数据科学项目,包括处理数据、开发和评估机器学习模型以及使用各种Python类库以表彰的方式显示作为API的模型。 你是否希望成为一名数据科学家呢?如果是的话,本教程将会为你快速掌握的概念和工具,并可以利用教程中所学习的技能以标准化的方式处理任何数据科学项目。本教程遵循一种使用的方法解决终端数据科学项目,从不同数据源提取数据到作为真正数据解决方案的API端点转换为机器学习模型。本教程不仅会帮助你理解各种数据科学项目概念,还会帮助你通过使用Python和相关类库以行业标准实现。 首先,你将会了解一个典型的数据科学项目声明周期的各个阶段,以及一个可以用于任何数据项目的标准化项目模板。然后,你将会学习使用各种Python生态系统中的标准类库,如Pandas、numPy、matplotlib、Scikit-learn,Flask以处理数据科学项目的不同阶段,如提取数据、清晰和处理数据、开发和评估机器学习模型。最后,你将深入了解机器学习模型。你还会在整个学习过程中处理一个案例。学习完本教程,你将扎实地掌握处理任何数据科学项目,并具备应用到各种Python类库创建你自己的数据科学解决方案的技能。
    wilde(特殊组-翻译)7个月前 (01-02)