| 書名: | Introduction to Data Science | |||
| 作者: | Gaoyan Ou | |||
| ISBN: | 9789811263897 | |||
| 出版社: | World Scientific (WS) | |||
| 出版日期: | 2023/12 | |||
|
#資訊
|
||||
| 定價: | ||||
| 售價: | 4464元 | |||
| 庫存: | 庫存: 1 | |||
| LINE US! | 詢問這本書 團購優惠、書籍資訊 等 | |||
Introduction to Data Science
定價:
4699
售價:
4464
現省:
235
| 付款方式: | 超商取貨付款 |
|
|
| 信用卡 |
|
||
| 線上轉帳 |
|
||
| 物流方式: | 超商取貨 | ||
| 宅配 | |||
| 門市自取 |
詳細資訊
The book systematically introduces the basic contents of data science, including data preprocessing and basic methods of data analysis, handling special problems (e.g. text analysis), deep learning, and distributed systems. In addition to systematically introducing the basic content of data science from a theoretical point of view, the book also provides a large number of data analysis practice cases.
為您推薦
類似書籍推薦給您
類似書籍推薦給您
類似書籍推薦給您
Data Mining and Analytics provides a broad and interactive overview of a rapidly growing field. The exponentially increasing rate at which data is generated creates a corresponding need for professionals who can effectively handle its storage, analysis, and translation. With a dual focus on concepts and operations, this text comprises a complete how-to and is an excellent resource for anyone considering the field. Case studies and hands-on activities incorporate real-world data sets and allow students the opportunity to exercise their new skills. Our Cloud Desktop integrates popular data mining tools, giving students a valuable familiarity with industry-standard applications. After defining the concepts of data mining and machine learning, Data Mining and Analytics delves into the types of databases, their respective relevance and popularity, and the trends that affect their use. The importance of data visualization for communication purposes is explored, as are the processes of data cleansing, clustering, and classification. Excel, SQL, NoSQL, Python, and R programming all receive in-depth treatments, supplemented with hands-on exercises. Operations covered in earlier chapters are given real-world context through a practical application to the current issues of “big data” and of text and image data mining. The text concludes by describing an analyst’s steps from planning through execution, ensuring that readers gain the technical know-how to launch, lead, or support a data project in the workplace.
華通書坊
