Data Science Crash Course for Beginners with Python: Fundamentals and Practices with Python

Book Description

Data Science Crash Course for Beginners with Python

Data Science is here to stay. The tremendous growth in the volume, velocity, and variety of data has a substantial impact on every aspect of a business. While data continues to grow exponentially, accuracy remains a problem. This is where data scientists play a decisive role. A data scientist analyzes data, discovers new insights, paints a picture, and creates a vision. And a competent data scientist will provide a business with the competitive edge it needs and address pressing business problems. Data Science Crash Course for Beginners with Python presents you with a hands-on approach to learn data science fast.

How Is This Book Different?

Every book by AI Publishing has been carefully crafted. This book lays equal emphasis on the theoretical sections as well as the practical aspects of data science. Each chapter provides the theoretical background behind the numerous data science techniques, and practical examples explain the working of these techniques. In the Further Reading section of each chapter, you will find the links to informative data science posts. This book presents you with the tools and packages you need to kick-start data science projects to resolve problems of practical nature. Special emphasis is laid on the main stages of a data science pipeline—data acquisition, data preparation, exploratory data analysis, data modeling and evaluation, and interpretation of the results. In the Data Science Resources section, links to data science resources, articles, interviews, and data science newsletters are provided. The author has also put together a list of contests and competitions that you can try on your own. Another added benefit of buying this book is you get instant access to all the learning material presented with this book— PDFs, Python codes, exercises, and references—on the publisher’s website. They will not cost you an extra cent. The datasets used in this book can be downloaded at runtime, or accessed via the Resources/Datasets folder. The author simplifies your learning by holding your hand through everything. The step by step description of the installation of the software you need for implementing the various data science techniques in this book is guaranteed to make your learning easier. So, right from the beginning, you can experiment with the practical aspects of data science. You’ll also find the quick course on Python programming in the second and third chapters immensely helpful, especially if you are new to Python. This book gives you access to all the codes and datasets. So, access to a computer with the internet is sufficient to get started.

The topics covered include:

• Introduction to Data Science and Decision Making
• Python Installation and Libraries for Data Science
• Review of Python for Data Science
• Data Acquisition
• Data Preparation (Preprocessing)
• Exploratory Data Analysis
• Data Modeling and Evaluation Using Machine Learning
• Interpretation and Reporting of Findings
• Data Science Projects
• Key Insights and Further Avenues

中文：

书名：Data Science Crash Course for Beginners with Python: Fundamentals and Practices with Python

使用Python的初学者数据科学速成课程

数据科学将继续存在。数据量、速度和种类的巨大增长对企业的方方面面都产生了重大影响。虽然数据继续呈指数级增长，但准确性仍然是一个问题。这就是数据科学家发挥决定性作用的地方。数据科学家分析数据，发现新见解，描绘图景，创造愿景。一位称职的数据科学家将为企业提供其所需的竞争优势，并解决紧迫的商业问题。使用Python的初学者数据科学速成课程它为您提供了快速学习数据科学的动手方法。

How Is This Book Different?

AI出版公司的每一本书都是精心制作的。这本书对数据科学的理论部分和实践方面给予了同等重视。每一章都提供了众多数据科学技术背后的理论背景，并通过实际例子解释了这些技术的工作原理。在Further Reading在每一章的每一节，你都会找到信息丰富的数据科学帖子的链接。本书为您提供了启动数据科学项目以解决实际问题所需的工具和包。特别强调数据科学管道的主要阶段–数据采集、数据准备、探索性数据分析、数据建模和评估以及结果解释。在数据科学资源部分，提供了指向数据科学资源、文章、访谈和数据科学时事通讯的链接。作者还整理了一份竞赛和竞赛清单，你可以自己尝试。购买这本书的另一个额外好处是，您可以立即访问出版商网站上随书提供的所有学习材料-PDF、Python代码、练习和参考资料。它们不会让你多花一分钱。本书中使用的数据集可以在运行时下载，也可以通过访问Resources/Datasets这个文件夹。作者通过牵着你的手学习每一件事来简化你的学习。本书对实现各种数据科学技术所需的软件安装进行了逐步描述，这将使您的学习变得更容易。因此，从一开始，你就可以尝试数据科学的实际方面。您还会发现第二章和第三章中关于Python编程的快速课程非常有帮助，特别是如果您还是一名新手的话。这本书为您提供了访问所有代码和数据集的权限。因此，连接到一台带有互联网的计算机就足以开始使用。

The topics covered include:

• 数据科学与决策导论
• 数据科学的Python安装和库
• Review of Python for Data Science
• Data Acquisition
• Data Preparation (Preprocessing)
• Exploratory Data Analysis
• 基于机器学习的数据建模与评估
• Interpretation and Reporting of Findings
• Data Science Projects
• Key Insights and Further Avenues