Data Science for Business
VonR.H Rizvi
Dieses E-Book entspricht möglicherweise nicht den Standards zur Barrierefreiheit und ist eventuell nicht vollständig mit unterstützenden Technologien kompatibel.
Data Science for Business is a best-selling guide that empowers professionals, entrepreneurs, and decision-makers with the knowledge to leverage data science for strategic business growth. Written by renowned expert R.H. Rizvi, this book provides a comprehensive exploration of data analytics, machine learning, and AI-driven decision-making, tailored specifically for business applications.
Covering fundamental concepts to advanced techniques, this book delves into:
✔ Supervised and unsupervised learning for business insights
✔ Predictive analytics for forecasting trends and optimizing operations
✔ Customer analytics, marketing optimization, and fraud detection
✔ Ethical considerations and data governance
✔ Emerging trends like AutoML, quantum computing, and edge analytics
With real-world case studies from industry giants like Amazon, Uber, and Coca-Cola, Data Science for Business offers actionable insights to help organizations make data-driven decisions with confidence. Whether you're a business leader, analyst, or aspiring data scientist, this book equips you with the tools to stay ahead in the competitive digital landscape.
Transform your business with the power of data science—get your copy today!
Details
- Veröffentlicht am
- Feb 27, 2025
- Sprache
- English
- Kategorie
- Business & Wirtschaft
- Copyright
- Alle Rechte vorbehalten - Standard-Urheberrechtslizenz
- Autoren/Mitwirkende
- Von (Autor): R.H Rizvi
Spezifikationen
- Format
- EPUB
Schlagwörter
Data Science for BusinessBusiness AnalyticsMachine Learning for BusinessAI in Business StrategyPredictive AnalyticsBig Data and Business IntelligenceBusiness Data Science ApplicationsMarketing AnalyticsCustomer Behavior AnalysisFinancial Data ScienceData-Driven Decision MakingAI-Powered Business GrowthData Science Case StudiesBusiness Forecasting ModelsData Governance and EthicsSupervised vs. Unsupervised Learning