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Students are rushing to master powerful machine learning techniques for improving decision-making and scaling analysis to immense datasets. Machine Learning with Python for Everyone brings together all they'll need to succeed: a practical understanding of the machine learning process, accessible code, skills for implementing that process with Python and the scikit-learn library, and real expertise in using learning systems intelligently.
Reflecting 20 years of experience teaching non-specialists, Dr. Mark Fenner teaches through carefully-crafted datasets that are complex enough to be interesting, but simple enough for non-specialists. Building on this foundation, Fenner presents real-world case studies that apply his lessons in detailed, nuanced ways. Throughout, he offers clear narratives, practical "code-alongs,” and easy-to-understand images -- focusing on mathematics only where it's necessary to make connections and deepen insight.
- All students need to succeed in data science with Python: process, code, and implementation
- Students will understand the machine learning process, leverage the powerful Python scikit-learn library, and master the algorithmic components of learning systems
- Integrates clear narrative, carefully designed Python code, images, and interesting, intelligible datasets
All you need to succeed in data science with Python: process, code, and implementation
- Understand the machine learning process, leverage the powerful Python scikit-learn library, and master the algorithmic components of learning systems
- Integrates clear narrative, carefully designed Python code, images, and interesting, intelligible datasets
- For wide audiences of analysts, managers, project leads, statisticians, developers, and students who want a quick jumpstart into data science
Students are rushing to master powerful machine learning techniques for improving decision-making and scaling analysis to immense datasets. Machine Learning with Python for Everyone brings together all they'll need to succeed: a practical understanding of the machine learning process, accessible code, skills for implementing that process with Python and the scikit-learn library, and real expertise in using learning systems intelligently.
Reflecting 20 years of experience teaching non-specialists, Dr. Mark Fenner teaches through carefully-crafted datasets that are complex enough to be interesting, but simple enough for non-specialists. Building on this foundation, Fenner presents real-world case studies that apply his lessons in detailed, nuanced ways. Throughout, he offers clear narratives, practical "code-alongs,” and easy-to-understand images -- focusing on mathematics only where it's necessary to make connections and deepen insight.
- All students need to succeed in data science with Python: process, code, and implementation
- Students will understand the machine learning process, leverage the powerful Python scikit-learn library, and master the algorithmic components of learning systems
- Integrates clear narrative, carefully designed Python code, images, and interesting, intelligible datasets
All you need to succeed in data science with Python: process, code, and implementation
- Understand the machine learning process, leverage the powerful Python scikit-learn library, and master the algorithmic components of learning systems
- Integrates clear narrative, carefully designed Python code, images, and interesting, intelligible datasets
- For wide audiences of analysts, managers, project leads, statisticians, developers, and students who want a quick jumpstart into data science
| Erscheinungsjahr: | 2019 |
|---|---|
| Medium: | Taschenbuch |
| Reihe: | Addison-Wesley Data & Analytics Series |
| Inhalt: | Kartoniert / Broschiert |
| ISBN-13: | 9780134845623 |
| ISBN-10: | 0134845625 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Fenner, Mark |
| Hersteller: | Pearson Education (US) |
| Verantwortliche Person für die EU: | preigu, Ansas Meyer, Lengericher Landstr. 19, D-49078 Osnabrück, mail@preigu.de |
| Maße: | 228 x 179 x 31 mm |
| Von/Mit: | Mark Fenner |
| Erscheinungsdatum: | 10.12.2019 |
| Gewicht: | 0,907 kg |
| Erscheinungsjahr: | 2019 |
|---|---|
| Medium: | Taschenbuch |
| Reihe: | Addison-Wesley Data & Analytics Series |
| Inhalt: | Kartoniert / Broschiert |
| ISBN-13: | 9780134845623 |
| ISBN-10: | 0134845625 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Fenner, Mark |
| Hersteller: | Pearson Education (US) |
| Verantwortliche Person für die EU: | preigu, Ansas Meyer, Lengericher Landstr. 19, D-49078 Osnabrück, mail@preigu.de |
| Maße: | 228 x 179 x 31 mm |
| Von/Mit: | Mark Fenner |
| Erscheinungsdatum: | 10.12.2019 |
| Gewicht: | 0,907 kg |
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