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This book focuses on the hands-on approach to learning Data Mining. It showcases how to use Python Packages to fulfill the Data Mining pipeline, which is to collect, integrate, manipulate, clean, process, organize, and analyze data for knowledge.
This book focuses on the hands-on approach to learning Data Mining. It showcases how to use Python Packages to fulfill the Data Mining pipeline, which is to collect, integrate, manipulate, clean, process, organize, and analyze data for knowledge.
Dr. Di Wu is an Assistant Professor of Finance, Information Systems, and Economics department of Business School, Lehman College. He obtained a Ph.D. in Computer Science from the Graduate Center, CUNY. Dr. Wu's research interests are 1) Temporal extensions to RDF and semantic web, 2) Applied Data Science, and 3) Experiential Learning and Pedagogy in business education. Dr. Wu developed and taught courses including Strategic Management, Databases, Business Statistics, Management Decision Making, Programming Languages (C++, Java, and Python), Data Structures and Algorithms, Data Mining, Big Data, and Machine Learning.
Section I. Data Wrangling 1. Data Collection. 2. Data Integration 3. Data Statistics 4. Data Visualization 5. Data Preprocessing Section II. Data Analysis 6. Classification 7. Regression 8. Clustering 9. Frequent Patterns 10. Outlier Detection
| Erscheinungsjahr: | 2024 |
|---|---|
| Fachbereich: | Programmiersprachen |
| Genre: | Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Seiten: | 390 |
| Inhalt: | Einband - flex.(Paperback) |
| ISBN-13: | 9781032598901 |
| ISBN-10: | 1032598905 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Wu, Di |
| Hersteller: | Taylor & Francis Ltd |
| Maße: | 179 x 254 x 27 mm |
| Von/Mit: | Di Wu |
| Erscheinungsdatum: | 10.04.2024 |
| Gewicht: | 0,766 kg |
Dr. Di Wu is an Assistant Professor of Finance, Information Systems, and Economics department of Business School, Lehman College. He obtained a Ph.D. in Computer Science from the Graduate Center, CUNY. Dr. Wu's research interests are 1) Temporal extensions to RDF and semantic web, 2) Applied Data Science, and 3) Experiential Learning and Pedagogy in business education. Dr. Wu developed and taught courses including Strategic Management, Databases, Business Statistics, Management Decision Making, Programming Languages (C++, Java, and Python), Data Structures and Algorithms, Data Mining, Big Data, and Machine Learning.
Section I. Data Wrangling 1. Data Collection. 2. Data Integration 3. Data Statistics 4. Data Visualization 5. Data Preprocessing Section II. Data Analysis 6. Classification 7. Regression 8. Clustering 9. Frequent Patterns 10. Outlier Detection
| Erscheinungsjahr: | 2024 |
|---|---|
| Fachbereich: | Programmiersprachen |
| Genre: | Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Seiten: | 390 |
| Inhalt: | Einband - flex.(Paperback) |
| ISBN-13: | 9781032598901 |
| ISBN-10: | 1032598905 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Wu, Di |
| Hersteller: | Taylor & Francis Ltd |
| Maße: | 179 x 254 x 27 mm |
| Von/Mit: | Di Wu |
| Erscheinungsdatum: | 10.04.2024 |
| Gewicht: | 0,766 kg |
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