Python

Computational thinking is increasingly gaining importance in modern biology, due to the unprecedented scale at which data is nowadays produced. Bridging the cultural gap between the biological and computational sciences, this book serves as an accessible introduction to computational concepts for students in the life sciences. It focuses on teaching algorithmic and logical thinking, rather than just the use of existing bioinformatics tools or programming. Topics are presented from a biological point of view, to demonstrate how computational approaches can be used to solve problems in biology such as biological image processing, regulatory networks, and sequence analysis. The book contains a range of pedagogical features to aid understanding, including real-world examples, in-text exercises, end-of-chapter problems, colour-coded Python code, and 'code explained' boxes. User-friendly throughout, Computational Thinking for Life Scientists promotes the thinking skills and self-efficacy req

Deep Learning in Practice helps you learn how to develop and optimize a model for your projects using Deep Learning (DL) methods and architectures.Key features: Demonstrates a quick review on Python, NumPy, and TensorFlow fundamentals.Explains and provides examples of deploying TensorFlow and Keras in several projects.Explains the fundamentals of Artificial Neural Networks (ANNs).Presents several examples and applications of ANNs.Learning the most popular DL algorithms features.Explains and provides examples for the DL algorithms that are presented in this book.Analyzes the DL network's parameter and hyperparameters.Reviews state-of-the-art DL examples.Necessary and main steps for DL modeling.Implements a Virtual Assistant Robot (VAR) using DL methods.Necessary and fundamental information to choose a proper DL algorithm.Gives instructions to learn how to optimize your DL model IN PRACTICE.This book is useful for undergraduate and graduate students, as well as practitioners in industry

Thoroughly updated with improved pedagogy, the fifth edition of this classic textbook continues to provide students with a clear and comprehensive introduction the fundamentals of the finite element method. New features include enhanced coverage of introductory topics in the context of simple 1D problems, providing students with a solid base from which to advance to 2D and 3D problems; expanded coverage of more advanced concepts, to reinforce students' understanding; over 30 additional solved problems; and downloadable MATLAB, Python, C, Javascript, Fortran and Excel VBA code packages, providing students with hands-on experience, and preparing them for commercial software. Accompanied by online solutions for instructors, this is the definitive text for senior undergraduate and graduate students studying a first course in the finite element method and finite element analysis, and for professional engineers keen to shore up their understanding of finite element fundamentals.

本書通過豐富的小提示、故事和關鍵術語的解釋，清晰地傳授各種編程技巧。書中包含Python、Java和Haskell的示例，無論你正在學習哪一種編程語言，都能幫助你獲得可移植的編程技能。本書主要面向學習編程課程的學生以及編程初學者和希望提升編程技藝的程序員，能幫助你在課程中取得好成績，並有助於養成良好的軟件工程習慣，從而開發出易讀且高效的好程序。

Qt支援C++、Python、Ruby、Perl等多種程式設計語言，常規使用者應用程式、多媒體、後端系統管理、汽車、國防、家電、移動設備等多個領域都在廣泛應用Qt。本書在全面闡述Qt基本功能的基礎上，對新增的功能和服務進行了重點介紹。同時運用大量示例，集中講解了應用程式的開發方法、技巧和必需的Qt API。讀者通過實際動手操作能夠迅速獲得業務中必備的相關知識與經驗，本書非常適合利用高級GUI和Op

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

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.

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.

本書的編寫目的是向讀者介紹大數據可視化的基本概念與應用。本書共 9 章，分別講述數據可視化概述、大數據可視化原理與方法、Excel 數據可視化、HTML5 前端可視化、Tableau 數據可視化、ECharts 數據可視化、Python 數據可視化、大屏數據可視化設計、R 語言數據可視化。本書將理論與實踐操作相結合，通過大量的案例幫助讀者快速瞭解和應用大數據可視化相關技術，並對重要的核心知識點加大

本書以信息技術工具與大數據分析為核心，通過詳實的案例組織，涵蓋了計算機硬件信息查看、Windows 10操作系統的使用、如何使用Internet常用功能、使用Python語言構建網絡爬蟲、使用Office 2016軟件工具包進行數據的存儲、處理和分析等內容。本書內容豐富，實例眾多，針對性強，敘述和分析透徹。每章都配有相關實驗及習題，具有可讀性、可操作性和實用性強等特點。特別是針對全國計算機等級考試

本書參照教育部計算機基礎課程的教學基本要求, 主要針對信息技術相關內容進行強化練習。全書共8章, 分為三部分: 第一部分 (第1-3章)為信息技術基礎, 介紹信息技術基礎知識, 包括軟件、硬件,操作系統和數據的表示與存儲等; 第二部分 (第4-6章)為數據處理, 介紹不同類型的數據處理過程和Python 程序設計基礎, 包括對結構化數據和非結構化數據的處理示例; 第三部分 (第7、8章) 為網絡新

本書結合作者多年教學和工作經驗，以兩個軟件著作權《計算機網絡安全智能雲端維護系統》和《超級星學生信息管理系統》為框架，自主研發了資產管理系統，精心設置系統Bug 以供學習者測試查找，從用例的編寫技巧、Bug 查找規律、Java 白盒測試、性能測試工具Loadrunner 的使用、用Python 進行自動化測試、測試計劃的撰寫、功能測試報告、性能測試報告等方面對軟件測試過程進行了全方位解讀。

本書為1+X職業技能等級證書(數據採集)配套教材，內容涵蓋1+X《數據採集職業技能等級標準》規定的技能要求。 本書按照數據採集系統的開發流程介紹了數據採集各個方面的開發技術，包括初識數據採集、分析網絡數據報、操作數據庫、製作慕課網首頁、抽取網頁數據、初識Python、爬取網絡數據、項目實戰：網絡爬蟲、創建Spring Boot項目、項目實戰：業務系統日誌數據採集、項目實戰：數據庫數據採集，詳細直

全書共8章, 分為三大部分: 第一部分 (第1-3章) 為信息技術基礎篇, 介紹信息技術基礎知識, 包括軟件硬件、操作系統和數據的表示與存儲等; 第二部分 (第4-6章) 為數據處理篇, 介紹不同類型數據的處理過程和Python程序設計基礎, 包括對結構化數據和非結構化數據的處理示例; 第三部分 (第7、8章) 為網絡新技術及信息安全篇, 介紹互聯網新技術及應用和信息安全基礎, 包括對新技術原理的

內容簡介本書由百度官方出品，百度公司CTO王海峰博士作序，張鈸院士、李未院士、百度集團副總裁吳甜聯袂推薦。本書遵循“內容全面、由淺入深、注重實踐”的原則，基於飛槳PaddlePaddle深度學習平臺，較為全面地覆蓋了學習深度學習技術所必須具備的基礎知識以及深度學習主要核心技術，包括相關的數學基礎、Python編程基礎、機器學習基礎以及正向/反向傳播算法、卷積神經網絡、循環神經網絡等，儘量做到讀懂一

本書以奇安信代碼衛士和代碼安全保障系統為基礎教學平臺，通過實踐教學，讓學生理解和掌握C、C++、Java、PHP和Python語言中可能出現的安全性漏洞；理解軟件發展過程中如果不採取規範和安全的編碼對系統造成的危害。培養學生養成規範和安全編碼的習慣，並能夠運用所學的技術和方法對企業軟件發展過程中典型的軟件安全問題進行安全分析、檢測和安全加固。

Python、C++ 搭配硬體一起用, 重現 IoT 駭客手法讓你懂！網際網路的快速發展, 讓資訊安全成為不能輕視的問題, 而物聯網 (IoT) 的出現與全面應用, 無疑又為網路資安增添更多隱憂。隨著物聯網裝置的進步, 不僅資訊蒐集能力越來越強, 提供的功能也更加完善, 然而享受便利生活的同時, 仍須正視這些貼近我們生活的裝置, 可能成為資安的缺口。因為有一種人可能正伺機而動, 他們就是 … "I

本書內容分為22章，包括Python類庫的安裝和使用、TensorFlow基本數據結構和使用、TensorFlow數據集的創建與讀取、人工神經網絡介紹、反饋神經網絡的理論基礎，深度學習模型的創建以及相關特性介紹等內容，並在本書各個模型部分特別介紹了模型調參的初步知識。本書強調理論聯繫實際，著重介紹了TensorFlow編程解決圖像識別的應用，提供了大量數據集供讀者使用，也以代碼的形式實現了深度學習

《大學計算機基礎：基於CDIO項目教學》共計6章內容，內容包括計算機組成、Python基礎、算法之美、數據庫及應用、網站設計、網絡與信息安全。《大學計算機基礎：基於CDIO項目教學》從教學內容和教學模式上努力創設高階課堂、對話課堂、開放課堂、知行合一、學思結合的課堂素材和方法，注重學科知識體系構建，以實際問題過程為載體，利用樹莓派計算機設置創客項目，通過CDIO項目學習網絡技術，進行一體化課程設計

使用scikit-learn探索各式機器學習模型，實作多種機器學習演算法 機器學習是近年的熱門話題，它將電腦科學與統計學結合在一起，打造智慧又有效率的模型。你可以使用機器學習提供的強大演算法和技術，來自動化任何分析模型，而scikit-learn正是一個優秀的Python機器學習函式庫，它可以實作多種機器學習演算法，是非常好用的工具。 本書詳細介紹一系列機器學習模型和scikit-learn的使用

With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology. Over 300 color illustrations are included and have been meticulously designed to enable an intuitive grasp of technical concepts, and over 100 in-depth coding exercises (in Python) provide a real understanding of crucial machine learning algorithms. A suite of online resources including sample code, data sets, interactive lecture slides, and a solutions manual are provided online, making this an ideal text both for grad

本書為《翻譯實踐指南》(TranslationPracticesExplained)系列叢書之一，是本地化翻譯領域的最新研究成果總結。本書緊跟行業技術的發展步伐，結合當前本地化行業發展的最新特點，從跨學科視角出發，將翻譯與本地化工程技術緊密結合，系統地講解了應用程序本地化的相關知識與技能。全書共分為七章，內容涵蓋國際化與本地化基礎、Python語言編程基礎、國際化問題和解決方案、應用程序本地化基礎

This third edition provides a concise yet approachable introduction to seismic theory, designed as a first course for graduate students or advanced undergraduate students. It clearly explains the fundamental concepts, emphasizing intuitive understanding over lengthy derivations, and outlines the different types of seismic waves and how they can be used to resolve Earth structure and understand earthquakes. New material and updates have been added throughout, including ambient noise methods, shear-wave splitting, back-projection, migration and velocity analysis in reflection seismology, earthquake rupture directivity, and fault weakening mechanisms. A wealth of both reworked and new examples, review questions and computer-based exercises in MATLAB®/Python give students the opportunity to apply the techniques they have learned to compute results of interest and to illustrate Earth's seismic properties. More advanced sections, which are not needed to understand the other material, are fla

This third edition provides a concise yet approachable introduction to seismic theory, designed as a first course for graduate students or advanced undergraduate students. It clearly explains the fundamental concepts, emphasizing intuitive understanding over lengthy derivations, and outlines the different types of seismic waves and how they can be used to resolve Earth structure and understand earthquakes. New material and updates have been added throughout, including ambient noise methods, shear-wave splitting, back-projection, migration and velocity analysis in reflection seismology, earthquake rupture directivity, and fault weakening mechanisms. A wealth of both reworked and new examples, review questions and computer-based exercises in MATLAB®/Python give students the opportunity to apply the techniques they have learned to compute results of interest and to illustrate Earth's seismic properties. More advanced sections, which are not needed to understand the other material, are fla

《自學是門手藝：沒有自學能力的人沒有未來》以自學Python編程為例，闡述了如何培養、習得自學能力，並運用自學能力在競爭激烈的社會中獲得一席之地，不斷地升級、進化，實現真正的成長。作為一本“硬核”的“雞湯”書，本書不僅僅以紙質的形式呈現，還配套了XUE.cn互動學習平臺。讀者不僅可以通過閱讀本書學到自學的方法，還能在XUE.cn上把這些方法付諸實踐，不斷練習、提升自己的技能，真正成為有積累、有前途

The Earth and environmental sciences are becoming progressively more quantitative due to the increased use of mathematical models and new data analysis techniques. This accessible introduction presents an overview of the mathematical methods essential for understanding Earth processes, providing an invaluable resource for students and early career researchers who may have missed (or forgotten) the mathematics they need to succeed as scientists. Topics build gently from basic methods such as calculus to more advanced techniques including linear algebra and differential equations. The practical applications of the mathematical methods to a variety of topics are discussed, ranging from atmospheric science and oceanography to biogeochemistry and geophysics. Including over 530 exercises and end-of-chapter problems, as well as additional computer codes in Python and MATLAB®, this book supports readers in applying appropriate analytical or computational methods to solving real research questi

A complete resource for finance students, this textbook presents the most common empirical approaches in finance in a comprehensive and well-illustrated manner that shows how econometrics is used in practice, and includes detailed case studies to explain how the techniques are used in relevant financial contexts. Maintaining the accessible prose and clear examples of previous editions, the new edition of this best-selling textbook provides support for the main industry-standard software packages, expands the coverage of introductory mathematical and statistical techniques into two chapters for students without prior econometrics knowledge, and includes a new chapter on advanced methods. Learning outcomes, key concepts and end-of-chapter review questions (with full solutions online) highlight the main chapter takeaways and allow students to self-assess their understanding. Online resources include extensive teacher and student support materials, including EViews, Stata, R, and Python so

《Python3.6編程實踐指南――計算機科學入門》(原書第3版)通過Python語言介紹了編程的基本知識，內容包括現代編程語言常用的各種數據存儲和基本處理方法，如數值、字符串、列表、集合、字典和文本信息；程序的條件和循環控制結構；函數的概念、定義和應用；編程方法以及測試和調試思路。本書也介紹了一些更高級的編程知識，包括面向對象的編程方法、圖形用戶界面的構建以及數據庫的處理。

本書為有關氣象信息處理與系統設計基礎領域的首部教材。內容包括氣象信息系統概述、氣象要素預報、氣象資料、氣象圖形圖像軟件GrADS、Fortran95程序設計、氣象信息系統開發實例、Python統計實例共7章內容。本書內容覆蓋面廣泛、豐富、體系嚴謹，體現了當前氣象信息技術的最新成果。本書信息量大，多採用案例、圖、表等方式進行表達，邏輯性強，易於讀者理解。本書將基礎性、時代性、系統性、啟發性、應用性融

《Raspberry Pi實戰入門（彩色圖解版）》一書通過大量彩圖和詳細的步驟，講解了有關樹莓派各方面的基礎知識，並且提供了手把手的入門指導。不僅如此，本書還涵蓋了樹莓派與Linux、網路、影音應用、Scratch、Python等相關的各類實際應用內容。全書採用四色大圖展示，每個步驟都在圖上標識出字母順序，並在圖片旁加上了詳細的講解說明。使得完全零基礎的讀者也可以跟著一步一步去做，從而輕鬆上手入門

Molecular simulation is a powerful tool in materials science, physics, chemistry and biomolecular fields. This updated edition provides a pragmatic introduction to a wide range of techniques for the simulation of molecular systems at the atomic level. The first part concentrates on methods for calculating the potential energy of a molecular system, with new chapters on quantum chemical, molecular mechanical and hybrid potential techniques. The second part describes methods examining conformational, dynamical and thermodynamical properties of systems, covering techniques including geometry-optimization, normal-mode analysis, molecular dynamics, and Monte Carlo simulation. Using Python, the second edition includes numerous examples and program modules for each simulation technique, allowing the reader to perform the calculations and appreciate the inherent difficulties involved in each. This is a valuable resource for researchers and graduate students wanting to know how to use atomic-sc

The simulation of physical systems requires a simplified, hierarchical approach which models each level from the atomistic to the macroscopic scale. From quantum mechanics to fluid dynamics, this book systematically treats the broad scope of computer modeling and simulations, describing the fundamental theory behind each level of approximation. Berendsen evaluates each stage in relation to its applications giving the reader insight into the possibilities and limitations of the models. Practical guidance for applications and sample programs in Python are provided. With a strong emphasis on molecular models in chemistry and biochemistry, this 2007 book will be suitable for advanced undergraduate and graduate courses on molecular modeling and simulation within physics, biophysics, physical chemistry and materials science. It will also be a useful reference to all those working in the field. Additional resources for this title including solutions for instructors and programs are available

★★★「程式設計不再孤軍奮戰，讓 AI 成為你的戰友！」★★★ ☆☆☆「用 VS Code + Copilot，讓寫程式變得像聊天一樣簡單！」☆☆☆ ★★★「專案實戰，立即上手，程式設計不再卡關！」★★★ 《寫程式的AI戰友 - VS Code x GitHub Copilot》帶你進入 AI 輔助程式設計的新世代。本書不僅教你如何用 VS Code 打造專屬開發環境，更完整揭示 GitHub Copilot 的秘密武器：自動補全、錯誤修正、重構優化、AI 對話寫程式，讓你像專業工程師一樣高效開發。 ◎本書特色： ☆從零開始：安裝 VS Code、設定 Python 環境、快速上手介面操作。 ☆AI 實戰：完整示範 Copilot 的用法——寫程式、除錯、重構、生成測試與文件。 ☆專案導向：涵蓋 CLI 工具、資料處理、API 整合等專案，邊學邊做，馬上能用。 ☆資料科學應用：結合 Jupyter Notebook、NumPy、Pandas、Matplotlib，立即展現 AI + Python 的威力。 ☆思維升級：教你如何成為「指揮 AI 的人」，而不是被 AI 主導，真正駕馭 Copilot。 ◎為何要讀這本書？ 在這個 AI 與程式設計緊密結合的時代，單靠背誦語法已經不足以讓你成為一位優秀的工程師。《寫程式的AI戰友 - VS Code x GitHub Copilot》將帶給你三大核心價值： 1. 掌握開發主流工具 VS Code 是全球最受歡迎的開發環境，本書完整介紹其安裝、操作與進階應用，讓你在最短時間內熟悉業界標準工具。 2. 學會駕馭 AI，而不是被 AI 取代 GitHub Copilot 能幫你寫程式，但本書更強調「思維升級」——如何正確下指令、判斷 AI 建議的正確性，培養「指揮 AI」的能力，避免淪為被動依賴。 3. 專案實戰，立即上手 從 CLI 工具到資料分析，從 API 整合到自動化報表，本書以專案導向學習，讓你邊學邊做，學到的技能馬上能應用在實際工作與專案中。 ◎ 讀完這本書，你將： ☆ 熟悉 VS Code 與 Python 的整合操作。 ☆ 能使用 GitHub Copilot 提升開發效率，寫程式就像與 AI 對話。 ☆ 具備判斷、比較與優化程式碼的能力。 ☆ 透過專案實戰累積經驗，快速從初學者邁向專業者。 這不只是

特色1. 數據處理和數據分析並重。針對金融大數據結構複雜、數據源和格式變換大的特點，充分講述SAS軟件DATA步強大的數據處理功能，強化金融數據處理內容。2. 將SAS數據分析能力強和R和Python靈巧和業界流行的特點相結合，建立融合SAS和R及Python的數據處理和分析教材構架，進行教學大綱、授課教案到教材、案例集和習題集等課程要件建設。3. 以《金融計量經濟學》為知識依托，以海通證券金融工程部、天風證券金融工程部、等有名券商量化金融策略為具體案例內容，以權益（股票）市場和債券（固定收益）市場為主要應用領域，以日數據（daily data）為主、高頻日內數據（intraday data）為輔，建立從數據搜集到數據清理、從投資組合到交易策略和算法交易等金融量化方法的教學案例。創新點1. 填補國內教材空白。作為一款權威的數據處理和統計分析軟件，多年來SAS在國內（尤其是銀行系統）得到了廣泛應用。已出版的教材多以操作和數據處理編程為主，針對金融數據處理和分析的書籍並不多見，尤其講解金融數據分析的SAS過程步（Proc step）的教材難以見到。本教材擬對分析金融時間序列的SAS過程進行詳細和全面的介紹，充分揭示SAS在處理和分析金融時間序列數據上的優勢，填補國內教材空白。2.SAS Viya平臺介紹和R、Python的軟件融合。SAS Viya 2016年推出以來，得到了很快的發展，出現了基於SAS Viya 云分析服務CAS的很多應用，國內一些金融機構也採用了SAS Viya構建自己的數據分析平臺。但國內介紹SAS Viya的書很少，沒有發現介紹利用SAS Viya中的ACTION進行金融數據分析的書籍。對SAS Viya的介紹以及利用SAS Viya中的Econometrics8.4 ACTION、Visal Statistical Analysis ACTION、Deep Learning ACTION等進行金融數據處理和分析的內容，是本教材的創新之處。

本書介紹了大數據挖掘與統計機器學習領域中最常用的模型和算法，包括最基礎的線性回歸與分類方法，以及模型評價與選擇的概念和方法，進而介紹了非線性回歸與分類方法(包括決策樹與組合方法、支持向量機、神經網絡以及在此基礎上發展的深度學習方法)。此外，介紹了無監督學習中的聚類方法，並給出了一個大數據分析的實例。除了方法的理論講解之外，我們還給出了每種方法的Python實現。

本書是一本機器學習實用指南，提供從基礎知識到進階技能的全面學習路徑。本書以淺顯 易懂的方式介紹了機器學習的基本概念和主要類型，並詳細介紹使用 Python 及常見的庫進行數 據處理和機器學習的實操。此外，介紹了數據預處理的詳細過程，最後通過若干典型案例加深 讀者對機器學習的理解。本書適合對機器學習感興趣的初學者，也可作為軟件開發人員、數據分析師、學術研究人員的參考書籍。

9780545451925 Alligator V.S. Python (Who Would Win?)9781338320268 Falcon V.S. Hawk (Who Would Win?)9781338320244 Green Ants V.S. Army Ants (Who Would Win?)9780545301701 Hammerhead V.S. Bull Shark (Who Would Win?)9780545451901 Hornet V.S. Wasp (Who Would Win?)9780545946100 Hyena V.S. Honey Badger (Who Would Win?)9780545946087 Jaguar V.S. Skunk (Who Would Win?)9780545160759 Killer Whale V.S. Great White Shark (Who Would Win?)9780545301718 Komodo Dragon V.S. King Cobra (Who Would Win?)9780545175715 Lion V.S. Tiger (Who Would Win?)9780545681216 Lobster V.S. Crab (Who Would Win?)9780545175722 Polar Bear V.S. Grizzly Bear (Who Would Win?)9780545681155 Rattlesnake V.S. Secretary Bird (Who Would Win?)9780545451918 Rhino V.S. Hippo (Who Would Win?)9780545301725 Tarantula V.S. Scorpion (Who Would Win?)9780545681278 Triceratops V.S. Spinosaurus (Who Would Win?)9780545175739 Tyrannosaurus Rex V.S. Velo

Migrate from pandas and scikit-Learn to PySpark to handle vast amounts of data and achieve faster data processing time. This book will show you how to make this transition by adapting your skills and leveraging the similarities in syntax, functionality, and interoperability between these tools. Distributed Machine Learning with PySpark offers a roadmap to data scientists considering transitioning from small data libraries (pandas/scikit-learn) to big data processing and machine learning with PySpark. You will learn to translate Python code from pandas/scikit-learn to PySpark to preprocess large volumes of data and build, train, test, and evaluate popular machine learning algorithms such as linear and logistic regression, decision trees, random forests, support vector machines, Na鴳e Bayes, and neural networks. After completing this book, you will understand the foundational concepts of data preparation and machine learning and will have the skills necessary to apply these methods using

軟硬結合、虛實交融，是當前互動媒體作品的重要特點。當物理世界和虛擬世界的信息實現互通時，學生們學習編程的興趣將會大大增加。Mind+是DFRobot推出的面向青少年的編程軟件，支持圖形化編程和Python代碼編程，支持眾多的開源硬件和擴展模塊。掌控板則是國產開源硬件項目“虛穀計劃”旗下的核心硬件，價格低廉且功能強大。 本書由兩位深度參與Mind+和掌控板開發的創客教育專家和多位經驗豐富的小學