Statistical Learning Using Neural Networks: A Guide for Statisticians and Data Scientists with Python
暫譯: 使用神經網絡的統計學習：針對統計學家和數據科學家的 Python 指南
de Braganca Pereira, Basilio, Radhakrishna Rao, Calyampudi, Borges De Oliveira, Fabio
相關主題
商品描述
Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks starting from the basics and increasingly demanding more effort from readers, who can learn the theory and its applications in statistical methods with concrete Python code examples. It presents a wide range of widely used statistical methodologies, applied in several research areas with Python code examples, which are available online. It is suitable for scientists and developers as well as graduate students.
Key Features:
- Discusses applications in several research areas
- Covers a wide range of widely used statistical methodologies
- Includes Python code examples
- Gives numerous neural network models
This book covers fundamental concepts on Neural Networks including Multivariate Statistics Neural Networks, Regression Neural Network Models, Survival Analysis Networks, Time Series Forecasting Networks, Control Chart Networks, and Statistical Inference Results.
This book is suitable for both teaching and research. It introduces neural networks and is a guide for outsiders of academia working in data mining and artificial intelligence (AI). This book brings together data analysis from statistics to computer science using neural networks.
商品描述(中文翻譯)
《使用神經網絡的統計學習：統計學家和數據科學家的 Python 指南》從基礎開始介紹人工神經網絡，並逐漸要求讀者付出更多努力，讀者可以通過具體的 Python 代碼示例學習理論及其在統計方法中的應用。它展示了多種廣泛使用的統計方法，並在幾個研究領域中應用，提供的 Python 代碼示例可在線獲得。該書適合科學家、開發人員以及研究生。
主要特點：
- 討論了幾個研究領域的應用
- 涵蓋了廣泛使用的統計方法
- 包含 Python 代碼示例
- 提供多種神經網絡模型
本書涵蓋了神經網絡的基本概念，包括多變量統計神經網絡、回歸神經網絡模型、生存分析網絡、時間序列預測網絡、控制圖網絡和統計推斷結果。
本書適合用於教學和研究。它介紹了神經網絡，並為在數據挖掘和人工智慧（AI）領域工作的非學術界人士提供指導。本書將統計學到計算機科學的數據分析通過神經網絡結合在一起。
作者簡介
Basilio de Bragança Pereira, DIC and PhD (Imperial Collage), is Professor Emeritus of the Federal University of Rio de Janeiro (UFRJ) where he has worked since 1970, in the Institute of Mathematics, Postgraduate School of Engineering (COPPE) and School of Medicine. Associate Professor at the Institute of Mathematics (1970-1989 and 1994-1997), Research Professor at COPPE (1970-present), Titular Professor of Applied Statistics at COPPE (1989-1994, retired), Titular Professor of Biostatistics at the School of Medicine (1998-2015, retired). Since 2018, he is a courtesy researcher at National Laboratory for Scientific Computing (LNCC).
Calyampudi Radhakrishna Rao, PhD and DSc (Cambridge), is Fellow of Royal Society known as C R Rao. He is Professor Emeritus at Pennsylvania State University and Research Professor at the University at Buffalo. Rao was awarded the US National Medal of Science in 2002 and the Guy Medal of the Royal Statistical Society in 1965, Silver, and in 2011, Gold. He is one of the top 10 Indian scientists of all time. He received 38 honorary doctoral degrees from universities in 19 countries. He is well-known for Cramér-Rao inequality, Rao-Blackwellization, Rao distance, Fisher-Rao metric, among other important concepts introduced by him.
Fábio Borges de Oliveira, Dr.-Ing. (TU Darmstadt), is Professor at National Laboratory for Scientific Computing (LNCC) where he gives lectures on cryptography and on artificial intelligence applied to security and privacy for PhD students. He also works in the areas of smart grids, high performance computing, and algorithms. From 1994 to 2002, he worked at Londrina State University, where he provided support to its Computational Mathematics Lab. He was lecturer and taught several subjects. He is an IEEE Senior Member and received the Latin America Distinguished Service Award by IEEE Communications Society in 2018.
作者簡介(中文翻譯)
Basilio de Bragança Pereira，DIC 和博士（帝國學院），是里約熱內盧聯邦大學（UFRJ）的名譽教授，自1970年以來一直在數學研究所、工程研究所（COPPE）和醫學院工作。曾任數學研究所副教授（1970-1989 和 1994-1997），COPPE 研究教授（1970年至今），應用統計學名譽教授（1989-1994，退休），醫學院生物統計學名譽教授（1998-2015，退休）。自2018年以來，他是國家科學計算實驗室（LNCC）的客座研究員。
Calyampudi Radhakrishna Rao，博士和科學博士（劍橋），是英國皇家學會的院士，知名於 C R Rao。他是賓夕法尼亞州立大學的名譽教授和布法羅大學的研究教授。Rao 於2002年獲得美國國家科學獎章，並於1965年和2011年分別獲得英國皇家統計學會的銀獎和金獎。他被認為是歷史上十大印度科學家之一。他獲得來自19個國家的38個榮譽博士學位。他以Cramér-Rao不等式、Rao-Blackwell化、Rao距離、Fisher-Rao度量等重要概念而聞名。
Fábio Borges de Oliveira，Dr.-Ing.（達姆施塔特工業大學），是國家科學計算實驗室（LNCC）的教授，為博士生講授密碼學和應用於安全與隱私的人工智慧課程。他還從事智能電網、高性能計算和算法等領域的研究。從1994年到2002年，他在倫德里納州立大學工作，為其計算數學實驗室提供支持。他曾擔任講師，教授多門課程。他是IEEE資深會員，並於2018年獲得IEEE通訊學會的拉丁美洲傑出服務獎。
