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▼a Subramanian, Vidya,
▼d 1978-,
▼e author.
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▼a Applied machine learning for data science practitioners /
▼c Vidya Subramanian, Apple, Cupertino, USA. |
| 260 | |
▼a Hoboken, New Jersey :
▼b Wiley,
▼c [2025] |
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▼a 2507 |
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▼a index
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▼a Includes index. |
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▼a Section 1: Introduction to Machine Learning & Data Science. Chapter 1 -- Data Science Overview -- Section 2: Data Preparation & Feature Engineering. Chapter 2 -- Data Preparation Overview. Chapter 3 -- Data Extraction. Chapter 4 -- ML Problem Framing. Chapter 5 -- Data Comprehension. Chapter 6 -- Data Quality Engineering. Chapter 7 -- Feature Optimization. Chapter 8 -- Feature Set Finalization -- Section 3: Build, Train, or Estimate the ML Model. Chapter 9 -- Regression. Chapter 10 -- Classification. Chapter 11 -- Ranking. Chapter 12 -- Clustering. Chapter 13 -- Patterns. Chapter 14 -- Time Series. Chapter 15 -- Anomaly Detection -- Section 4: Model Performance Optimization. Chapter 16 -- Model Optimization & Model Selection. Chapter 17 -- Decision Tree. Chapter 18 -- Ensemble Methods -- Section 5: ML Ethics. Chapter 19 -- ML Ethics -- Section 6: Productionalize the Machine Learning Model. Chapter 20 -- Deploy and Monitor Models. |
| 520 | |
▼a "Welcome to the world of Data Science! The world has witnessed remarkable technological advancements in the past decade, often taken for granted. From facial recognition unlocking our phones to the emergence of self-driving cars, Data Science applications have surpassed our wildest imaginations. Large Language Models (LLMs) have become an integral part of our lives, enabling content generation from prompts. Data is already transforming how we live and work, and its importance will only increase with new data being generated every day"-- Provided by publisher. |
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▼a Description based on print version record and CIP data provided by publisher; resource not viewed. |
| 590 | |
▼a WorldCat record variable field(s) change: 650 |
| 650 | 0 |
▼a Machine learning. |
| 650 | 0 |
▼a Quantitative research
▼x Data processing. |
| 650 | 0 |
▼a Mathematical statistics
▼x Data processing. |
| 650 | 0 |
▼a Machine learning
▼x Industrial applications. |
| 650 | 0 |
▼a Probabilities. |
| 650 | 0 |
▼a Electronic books. |
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▼a probability.
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▼a statistics.
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▼i Print version:
▼a Subramanian, Vidya, 1978-
▼t Applied machine learning for data science practitioners
▼d Hoboken, New Jersey : Wiley, [2025]
▼z 9781394155378
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| 776 | 08 |
▼i Print version:
▼z 9781394155378 |
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