Essential Math for Data Science: Take Control of Your Data with Fundamental Linear Algebra, Probability, and Statistics - Thomas Nield

Descriere YEO:

Essential Math for Data Science: - Disponibil la libris.ro

Pe YEO găsești Essential Math for Data Science: de la Thomas Nield, în categoria Computers.

Indiferent de nevoile tale, Essential Math for Data Science: Take Control of Your Data with Fundamental Linear Algebra, Probability, and Statistics - Thomas Nield din categoria Computers îți poate aduce un echilibru perfect între calitate și preț, cu avantaje practice și moderne.

Preț: 327.31 Lei

Caracteristicile produsului Essential Math for Data Science:

• Brand: Thomas Nield
• Categoria: Computers
• Magazin: libris.ro
• Ultima actualizare: 15-12-2024 01:42:32

Comandă Essential Math for Data Science: Online, Simplu și Rapid

Prin intermediul platformei YEO, poți comanda Essential Math for Data Science: de la libris.ro rapid și în siguranță. Bucură-te de o experiență de cumpărături online optimizată și descoperă cele mai bune oferte actualizate constant.

Descriere magazin:
Master the math needed to excel in data science, machine learning, and statistics. In this book author Thomas Nield guides you through areas like calculus, probability, linear algebra, and statistics and how they apply to techniques like linear regression, logistic regression, and neural networks. Along the way you\'ll also gain practical insights into the state of data science and how to use those insights to maximize your career. Learn how to: Use Python code and libraries like SymPy, NumPy, and scikit-learn to explore essential mathematical concepts like calculus, linear algebra, statistics, and machine learning Understand techniques like linear regression, logistic regression, and neural networks in plain English, with minimal mathematical notation and jargon Perform descriptive statistics and hypothesis testing on a dataset to interpret p-values and statistical significance Manipulate vectors and matrices and perform matrix decomposition Integrate and build upon incremental knowledge of calculus, probability, statistics, and linear algebra, and apply it to regression models including neural networks Navigate practically through a data science career and avoid common pitfalls, assumptions, and biases while tuning your skill set to stand out in the job market