Python

本書共23章，介紹了新商科、新文科本科生能用到的大數據可視化技術與方法，以及常見的大數據可視化應用案例。本書簡單實用，在介紹每一種大數據可視化工具時，兼顧在線工具可視化和編程可視化兩種方式：利用在線工具，可以用不編程的方法實現大數據可視化；對於Python編程部分，採用模板化知識講授，只需少量替換模板中的語句即可將其應用到其他場景。 本書是為新商科、新文科類專業師生定制的教材，讓沒有編程基礎的學生能懂、會用，讓非計算機專業出身的教師可以學通、講授。同時，本書也可供其他大數據可視化的初學者參考。

如今，所有領域的資料量都在急劇增長。如何才能高效利用這些資料呢？本書介紹了開源集群計算系統Apache Spark，它可以加速資料分析的實現和運行。利用Spark，你可以用Python、Java以及Scala的簡易API來快速操控大規模資料集。 本書由Spark開發者編寫，可以讓資料科學家和工程師即刻上手。你能學到如何使用簡短的代碼實現複雜的並行作業，還能瞭解從簡單的批次處理作業到流處理以及機器學

本研究以內蒙古為研究區域，對內蒙古不同草地類型的可燃物進行野外調查和室內燃燒實驗，分析內蒙古草原可燃物燃燒特性、揭示草原火時空特徵，再利用室內實驗得出的碳排放數據估算內蒙古草原火碳排放情況。 將草原火行為模型參數本地化處理．構建適用於內蒙古草原火行為的模型，利用Python程序語言基於CA和GIS技術實現對草原火蔓延的模擬， 具體從以下5個方面展開。

本書主要介紹大資料分析與應用，包括資料驅動程序設計、資料前處理、統計機器學習基礎、無監督式學習、監督式學習、其他學習方式（集成學習、深度學習、強化學習）等6章內容。本書特色：文字說明、程式碼與執行結果等交叉呈現，有助於閱讀理解；提供來自不同領域的資料處理與分析範例；同時掌握資料分析兩大主流工具—— R 與 Python；凸顯第四代與第三代程式語言的不同之處。本書讀者物件：計算機、人工智能、大資料等相關專業的本科生、研究生，對大資料分析與應用感興趣的社會讀者，以及大資料分析與應用行業的工程技術人員。

Linear algebra is something all mathematics undergraduates and many other students, in subjects ranging from engineering to economics, have to learn. The fifth edition of this hugely successful textbook retains the quality of earlier editions while at the same time seeing numerous minor improvements and major additions. The latter include: a new chapter on singular values and singular vectors, including ways to analyze a matrix of data; a revised chapter on computing in linear algebra, with professional-level algorithms and code that can be downloaded for a variety of languages; a new section on linear algebra and cryptography; and a new chapter on linear algebra in probability and statistics. A dedicated and active website also offers solutions to exercises as well as new exercises from many different sources (e.g. practice problems, exams, development of textbook examples), plus codes in MATLAB, Julia, and Python.

本書以俄羅斯方塊遊戲作為實戰案例分析了遊戲中的基礎元素。根據分析所得的數據結構和功能，依次切換使用C、Java、Python、JavaScript這4門不同的編程語言來開發俄羅斯方塊遊戲，並以此為契機，探討如何培養通用的編程能力，如何按需切換使用不同的編程語言。本書共6章。第1章介紹了跨語言編程訓練的背景和意義，以及本書中將用到的編程語言。第2章從基礎、規則和進階3個層面分析俄羅斯方塊遊戲的邏輯，從而得出關鍵的數據結構和功能。第3～6章分別使用C、Java、Python、JavaScript這4門語言，依據相同的邏輯，並結合語言自身的特點，依次編碼實現俄羅斯方塊遊戲。本書可作為計算機科學與技術、軟件工程、網絡工程、網絡空間安全、電子信息技術、通信工程等專業本科生和研究生的拓展參考書，也可以作為培訓機構的參考資料。本書定位於希望快速掌握多門編程語言，有一定編程經驗的自學者、學生、初入行的工程師。對於在相關IT企業中從事軟件研發的資深工程師，本書也具有很好的參考價值。

數據孤島和隱私保護已經成為制約人工智能發展的關鍵因素。聯邦學習作為一種新型的隱私保護計算方案，在數據不出本地的前提下，能有效聯合各參與方聯合建模，從而實現“共同富裕”，成為當下人工智能領域備受關注的熱點。本書以實戰為主（包括對應用案例的深入講解和代碼分析），兼顧對理論知識的系統總結。全書由五部分共19 章構成。第一部分簡要介紹了聯邦學習的理論知識；第二部分介紹如何使用Python 和FATE 進行

本書是面向高級人工智能人才培養的高等學校人工智能相關專業規劃教材中的一本，通過梳理人工智能涉及的相關數學理論，並通過Python實現相關案例，使抽象的理論具體化，從而加深讀者對數學的感性認識，提高讀者對數學理論的理解能力。本書首先介紹了人工智能所需的基礎數學理論，然後根據數學內容的邏輯順序，以微積分、線性代數、概率論、數理統計為基礎，對函數逼近、最優化理論、信息論、圖論

《人工智能專業英語教程/大數據與人工智能技術叢書》是人工智能專業英語教材，涉及人工智能基礎、強人工智能與弱人工智能、人工智能應用領域、常用搜索算法、軟件與Python編程語言、知識系統與知識庫、專家系統和推理引擎、機器學習與深度學習、決策樹、人工神經網絡和模糊神經網絡、監督學習與無監督學習、人工智能安全、大數據與人工智能、雲計算與人工智能、普適計算、人工智能與智慧城市等多個方面。 《人工智能專業

This textbook provides future data analysts with the tools, methods, and skills needed to answer data-focused, real-life questions; to carry out data analysis; and to visualize and interpret results to support better decisions in business, economics, and public policy. Data wrangling and exploration, regression analysis, machine learning, and causal analysis are comprehensively covered, as well as when, why, and how the methods work, and how they relate to each other. As the most effective way to communicate data analysis, running case studies play a central role in this textbook. Each case starts with an industry-relevant question and answers it by using real-world data and applying the tools and methods covered in the textbook. Learning is then consolidated by 360 practice questions and 120 data exercises. Extensive online resources, including raw and cleaned data and codes for all analysis in Stata, R, and Python, can be found at www.gabors-data-analysis.com.

This textbook provides future data analysts with the tools, methods, and skills needed to answer data-focused, real-life questions; to carry out data analysis; and to visualize and interpret results to support better decisions in business, economics, and public policy. Data wrangling and exploration, regression analysis, machine learning, and causal analysis are comprehensively covered, as well as when, why, and how the methods work, and how they relate to each other. As the most effective way to communicate data analysis, running case studies play a central role in this textbook. Each case starts with an industry-relevant question and answers it by using real-world data and applying the tools and methods covered in the textbook. Learning is then consolidated by 360 practice questions and 120 data exercises. Extensive online resources, including raw and cleaned data and codes for all analysis in Stata, R, and Python, can be found at www.gabors-data-analysis.com.

Keras是一個用Python編寫的開源人工神經網絡庫，可以作為TensorFlow、CNTK和Theano的高階應用程序接口，進行深度學習模型的設計、調試、評估、應用和可視化。本書從初學者的角度出發，為讀者構建一個完整的Keras技術體系。本書共分為9章，主要內容包括深度學習框架Keras的背景、搭建學習環境、深度學習的理論基礎、卷積層與MNIST實戰、多層感知機與MNIST實戰、TensorFlow Datasets和TensorBoard、ResNet及其兄弟ResNext，最後是兩個項目實戰案例——詞嵌入與情感分類。本書既適合Keras深度學習初學者、深度學習算法技術人員閱讀，也適合作為高等院校與培訓機構人工智能相關專業的師生參考。

Numerical relativity has emerged as the key tool to model gravitational waves - recently detected for the first time - that are emitted when black holes or neutron stars collide. This book provides a pedagogical, accessible, and concise introduction to the subject. Relying heavily on analogies with Newtonian gravity, scalar fields and electromagnetic fields, it introduces key concepts of numerical relativity in a context familiar to readers without prior expertise in general relativity. Readers can explore these concepts by working through numerous exercises, and can see them 'in action' by experimenting with the accompanying Python sample codes, and so develop familiarity with many techniques commonly employed by publicly available numerical relativity codes. This is an attractive, student-friendly resource for short courses on numerical relativity, as well as providing supplementary reading for courses on general relativity and computational physics.

Numerical relativity has emerged as the key tool to model gravitational waves - recently detected for the first time - that are emitted when black holes or neutron stars collide. This book provides a pedagogical, accessible, and concise introduction to the subject. Relying heavily on analogies with Newtonian gravity, scalar fields and electromagnetic fields, it introduces key concepts of numerical relativity in a context familiar to readers without prior expertise in general relativity. Readers can explore these concepts by working through numerous exercises, and can see them 'in action' by experimenting with the accompanying Python sample codes, and so develop familiarity with many techniques commonly employed by publicly available numerical relativity codes. This is an attractive, student-friendly resource for short courses on numerical relativity, as well as providing supplementary reading for courses on general relativity and computational physics.

本書以Python語言和Tensorflow為工具，由淺入深地講述了深度學習程序設計的基本原理、算法和思考問題的方法，內容包括自頂向下的程序設計、遞歸程序設計、面向對象的程序設計、反向傳播算法、三層神經網絡、卷積神經網絡、循環神經網絡、生成式對抗網絡和目標檢測等。本書重在研究代碼背後深刻的計算機理論和數學原理，試圖說明代碼是對理論和思想的實現手段，而不是目的。學以致用是本書的宗旨，提高讀者編程水平