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Data Science: Foundations, Systems & AI: A Practical Guide to Statistics, Machine Learning, Deep Learning, Generative AI, MLOps, and Real-World Data Science - Softcover
Inhaltsangabe
Master Data Science From Foundations to Modern AI
Data Science: Foundations, Systems & AI is a practical, end-to-end guide designed for learners who want to understand not only data science fundamentals, but also the modern AI systems transforming the industry.
Starting with mathematics, statistics, Python, data preparation, and exploratory analysis, the book progressively moves into machine learning, advanced modeling, deep learning, NLP, foundation models, large language models, generative AI, RAG, AI agents, and production ML systems.
You'll learn how to:
- Understand and formulate real-world data problems
- Work with Python and data-processing workflows
- Apply statistics and machine learning
- Build and evaluate predictive models
- Understand deep learning and transformers
- Work with NLP and embeddings
- Build LLM and generative-AI applications
- Design RAG systems
- Understand AI agents and tool calling
- Deploy and monitor ML models
- Apply MLOps principles
- Detect data and model drift
- Design production AI systems
- Prepare for data-science and ML interviews
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Data Science
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Data Science: Foundations, Systems & AI: A Practical Guide to Statistics, Machine Learning, Deep Learning, Generative AI, MLOps, and Real-World Data Science
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Data Science : Foundations, Systems & AI: A Practical Guide to Statistics, Machine Learning, Deep Learning, Generative AI, MLOps, and Real-World Data Science
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Taschenbuch. Zustand: Neu. Neuware - Master Data Science From Foundations to Modern AIData Science: Foundations, Systems & AI is a practical, end-to-end guide designed for learners who want to understand not only data science fundamentals, but also the modern AI systems transforming the industry.Starting with mathematics, statistics, Python, data preparation, and exploratory analysis, the book progressively moves into machine learning, advanced modeling, deep learning, NLP, foundation models, large language models, generative AI, RAG, AI agents, and production ML systems.You'll learn how to: - Understand and formulate real-world data problems- Work with Python and data-processing workflows- Apply statistics and machine learning- Build and evaluate predictive models- Understand deep learning and transformers- Work with NLP and embeddings- Build LLM and generative-AI applications- Design RAG systems- Understand AI agents and tool calling- Deploy and monitor ML models- Apply MLOps principles- Detect data and model drift- Design production AI systems- Prepare for data-science and ML interviews. Bestandsnummer des Verkäufers 9798193860297
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