Acabei de saber por um amigo sobre o Marcus Nunes’ Blog que a editora Springer disponibilizou mais de 500 livros gratuitamente.
Boa oportunidade de fazer um backup e treinar raspagem de dados.
Basta visitar o site e baixar, sem sequer necessitar fazer cadastro. A lista completa de livros está no site do Marcus Nunes emplanilha do Excel, mas abaixo eu coloquei a listagem de livros de Matemática e Estatística. O site dele é muito bom. aqui está o link. https://marcusnunes.me/posts/
[1] “A Beginner’s Guide to R”
[2] “A Modern Introduction to Probability and Statistics”
[3] “A Primer on Scientific Programming with Python”
[4] “A Pythagorean Introduction to Number Theory”
[5] “Abstract Algebra”
[6] “Algebra”
[7] “All of Statistics”
[8] “An Introduction to Statistical Learning”
[9] “Applied Linear Algebra”
[10] “Applied Multivariate Statistical Analysis”
[11] “Applied Partial Differential Equations”
[12] “Applied Predictive Modeling”
[13] “Applied Quantitative Finance”
[14] “Bayesian and Frequentist Regression Methods”
[15] “Bayesian Essentials with R”
[16] “Brownian Motion, Martingales, and Stochastic Calculus”
[17] “Business Statistics for Competitive Advantage with Excel 2016” [18] “Calculus With Applications”
[19] “Classical Fourier Analysis”
[20] “Complex Analysis”
[21] “Design and Analysis of Experiments”
[22] “Differential Equations and Their Applications”
[23] “Discrete Mathematics”
[24] “Elementary Analysis”
[25] “Fundamentals of Clinical Trials”
[26] “Introduction to Partial Differential Equations”
[27] “Introduction to Partial Differential Equations”
[28] “Introduction to Smooth Manifolds”
[29] “Introduction to Statistics and Data Analysis”
[30] “Introduction to Time Series and Forecasting”
[31] “Introductory Statistics with R”
[32] “Introductory Time Series with R”
[33] “Linear Algebra”
[34] “Linear Algebra Done Right”
[35] “Methods of Mathematical Modelling”
[36] “Modeling Life”
[37] “Multivariate Calculus and Geometry”
[38] “Numerical Optimization”
[39] “Ordinary Differential Equations”
[40] “Partial Differential Equations”
[41] “Probability”
[42] “Probability Theory”
[43] “Probability Theory”
[44] “Proofs from THE BOOK”
[45] “Quantum Theory for Mathematicians”
[46] “Reading, Writing, and Proving”
[47] “Real Analysis”
[48] “Regression Modeling Strategies”
[49] “Representation Theory”
[50] “Statistical Analysis and Data Display”
[51] “Statistical Learning from a Regression Perspective”
[52] “Statistics and Data Analysis for Financial Engineering”
[53] “Survival Analysis”
[54] “The Elements of Statistical Learning”
[55] “Time Series Analysis”
[56] “Understanding Analysis”
[57] “Understanding Statistics Using R”