SKU/Artículo: AMZ-B0G642TD3L
WORKBOOK Linear Algebra for MBA: VOLUME I: FOUNDATIONS (MBA Self-Study Intelligence Series 9)
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Kindle
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0.76 kg
0.76 kg
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Amazon
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Sobre este producto
- Linear Algebra for Business Analytics, Economics, and Decision Sciences: Linear algebra powers everything modern businesses care about: machine learning algorithms, portfolio optimization, supply chain management, customer analytics, recommendation systems, and data-driven decision-making. Yet most textbooks are written for mathematicians, filled with abstract proofs that leave business professionals cold. This workbook is different. 180 Problems. 18 Chapters. Divided over Two Volumes. This is Volume I: Foundations. Zero Abstract Nonsense. Every single problem is grounded in real business scenarios. You won't calculate eigenvalues for arbitrary matrices—you'll compute them to analyze market share dynamics. You won't solve abstract equations—you'll balance supply-demand networks and forecast sales. You won't manipulate matrices without purpose—you'll build portfolio models, analyze customer surveys, and understand how Netflix recommendations actually work. What You'll Master: • Foundations (Chapters 1-3): Vectors, matrices, and operations applied to portfolios, supply chains, and customer similarity • Core Methods (Chapters 4-6): Systems of equations, regression (the math behind Excel's trendlines), and optimization • Dimension Reduction (Chapters 7-9): PCA (reduce 100 attributes to 3 key factors), Markov chains (predict market share), SVD (recommendation systems) Volume II: Advanced Applications: • Networks & Finance (Chapters 10-12): Supply chain graphs, modern portfolio theory (Markowitz optimization), input-output economics • Strategic Decisions (Chapters 13-14): Game theory (Nash equilibrium, when to compete vs. cooperate), linear programming (shadow prices, Simplex method) • Advanced Theory (Chapters 15-16): Eigenvalues (stability analysis, PageRank), matrix calculus (how neural networks learn, where OLS formulas come from) • Modern Applications (Chapters 17-18): Factor models (asset pricing, survey analysis), machine learning fundamentals (regression, classification, regularization, neural networks) Excel-Focused with Python/R Pathways Most business professionals work in Excel. This workbook teaches you MMULT, MINVERSE, Solver, Data Analysis tools—the Excel functions that do linear algebra. Specific formulas. Specific cell references. Ready to use Monday morning. But when Excel isn't enough (neural networks, large-scale optimization, advanced matrix computations), we show you the Python or R code—usually 10-20 lines with explanations. No programming background required. Detailed Solutions That Actually Teach Every problem includes complete solutions showing: • Step-by-step calculations • Business interpretation of results • Common mistakes to avoid • When to use which method • Excel implementation with specific formulas • When to transition to Python/R. Perfect For: ✓ MBA Students taking analytics, operations research, quantitative marketing courses ✓ Working Professionals in analytics, consulting, finance, operations who need mathematical foundations ✓ Managers & Executives who need to understand what data scientists are doing ✓ Career Changers moving into analytics or data science ✓ Self-Learners who recognize linear algebra as the language of AI/ML What Makes This Different: ✗ No abstract proofs for their own sake ✓ Every problem has business context ✓ Understand why methods work and when to use them From Beginner to Advanced Linear algebra is hard. But it's also incredibly powerful. And with 180 carefully crafted problems spanning every business application, you have everything you need to master it. Scroll up and click "Buy Now" to start building your competitive advantage today. Dr. Cornelis P.M. van Houte
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