Description
| Product ID: | 9780136624356 |
| Product Form: | Paperback / softback |
| Country of Manufacture: | US |
| Series: | Addison-Wesley Data & Analytics Series |
| Title: | Foundational Python for Data Science |
| Authors: | Author: Kennedy Behrman |
| Page Count: | 256 |
| Subjects: | Programming and scripting languages: general, Programming & scripting languages: general, Data warehousing, Data mining, Data warehousing, Data mining |
| Description: | Select Guide Rating Data science and machine learning—two of the world''s hottest fields—are attracting talent from a wide variety of technical, business, and liberal arts disciplines. Python, the world''s #1 programming language, is also the most popular language for data science and machine learning. This is the first guide specifically designed to help millions of people with widely diverse backgrounds learn Python so they can use it for data science and machine learning. Leading data science instructor and practitioner Kennedy Behrman first walks through the process of learning to code for the first time with Python and Jupyter notebook, then introduces key libraries every Python data science programmer needs to master. Once you''ve learned these foundations, Behrman introduces intermediate and applied Python techniques for real-world problem-solving. Throughout, Foundational Python for Data Science presents hands-on exercises, learning assessments, case studies, and more—all created with Colab (Jupyter compatible) notebooks, so you can execute all coding examples interactively without installing or configuring any software. Data science and machine learning—two of the world''s hottest fields—are attracting talent from a wide variety of technical, business, and liberal arts disciplines. Python, the world''s #1 programming language, is also the most popular language for data science and machine learning. This is the first guide specifically designed to help students with widely diverse backgrounds learn foundational Python so they can use it for data science and machine learning. This book is catered to introductory-level college courses on data science. Leading data science instructor and practitioner Kennedy Behrman first walks through the process of learning to code for the first time with Python and Jupyter notebook, then introduces key libraries every Python data science programmer needs to master. Once students have learned these foundations, Behrman introduces intermediate and applied Python techniques for real-world problem-solving. Throughout, Foundational Python for Data Science presents hands-on exercises, learning assessments, case studies, and more—all created with Colab (Jupyter compatible) notebooks, so students can execute all coding examples interactively without installing or configuring any software. |
| Imprint Name: | Pearson |
| Publisher Name: | Pearson Education (US) |
| Country of Publication: | GB |
| Publishing Date: | 2022-01-24 |
