Natural Language Processing with Python

「TQC+ 程式語言Python 3」係為TQC+ 軟體設計領域之程式語言認證能力鑑定，以實務操作方式進行認證，評核符合企業需求的新時代專業設計人才。亦為考核「程式設計專業人員」必備專業技能之一。 本書遵循專業考科「TQC+ 程式語言Python 3」技能規範架構撰寫，符合鑑定的命題趨勢。 1.內容淺顯易懂，結合理論與實務，達到技術的傳承及表達，符合實務運用需求。 2.採由淺入深之安排，適合相關科

「TQC+ 網頁資料擷取與分析Python 3」係為TQC+ 軟體設計領域之程式語言認證能力鑑定，以實務操作方式進行認證，評核符合企業需求的新時代專業設計人才。亦為考核「程式設計專業人員」必備專業技能之一。1.內容淺顯易懂，結合理論與實務，達到技術的傳承及表達，符合實務運用需求。2.涵蓋知識觀念和範例練習，作為培養網頁資料擷取與分析Python 3能力之最佳讀本。3.本書分成五個部分，包含「Pyt

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A delightful touchy-feely book with simple, repetitive text.Bright, colourful illustrations with textures to touch and feel on every page.Helps very young children develop language and sensory skills.

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此套碼會以散裝單本出貨，包含以下書籍：9781557996558Daily Language Review (2015 revised edition), Grade 1 Teacher Edition9781557996565Daily Language Review (2015 revised edition), Grade 2 Teacher Edition9781557996572Daily Language Review (2015 revised edition), Grade 3 Teacher Edition9781557996589Daily Language Review (2015 revised edition), Grade 4 Teacher Edition9781557996596Daily Language Review (2015 revised edition), Grade 5 Teacher Edition9781557997920Daily Language Review (2015 revised edition), Grade 6 Teacher Edition9781608236565Daily Language Review (2015 revised edition), Grade 7 Teacher Edition9781608236572Daily Language Review (2015 revised edition), Grade 8 Teacher Edition

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Natural Language Processing (NLP) offers unbounded opportunities for solving interesting problems in artificial intelligence, making it the latest frontier for developing intelligent, deep learning-b

This book offers an introduction to modern natural language processing using machine learning, focusing on how neural networks create a machine interpretable representation of the meaning of natural l

Natural Language Processing (NLP) is a scientific discipline which is found at the intersection of fields such as Artificial Intelligence, Linguistics, and Cognitive Psychology. This book presents in

A broad overview of natural language processing in affective computing is given by this title. Its goal is to familiarize the reader with current approaches in affective computing as well as the most

This book presents a unique opportunity for constructing a consistent image of collaborative manual annotation for Natural Language Processing (NLP). NLP has witnessed two major evolutions in the pas

For graduate students and budding researchers in natural language processing, computer scientists review current research and practices in computational techniques to automate any kind of human-like p

This book examines key issues in designing semantics-oriented natural language processing systems. A broad conceptual framework for describing structured meanings of NL-texts is obtained by defining

Written for researchers and practitioners in the field of biomedicine, this collection of research articles stressed the need for broader applications of natural language processing (NLP) for a more f

Independent researcher Georgiev focuses on written language rather than spoken as he examines the discipline and results of natural language processing as it is most closely associated with computer-u

Christian Jacquemin shows how the power of natural language processing (NLP) can be used to advance text indexing and information retrieval (IR). In this book Christian Jacquemin shows how the power

One of the aims of Natural Language Processing is to facilitate .the use of computers by allowing their users to communicate in natural language. There are two important aspects to person-machine comm

✧✦ 初學 Python 的最佳教材，第一次寫程式就上手！ ✦✧✧✦ 從基礎語法到生成式 AI 應用，打穩 Vibe Coding的關鍵能力 ✦✧身處在 vibe coding 的時代，在當前要能順利和 AI 協作，程式能力依然是不可或缺的。同時，在大數據、人工智慧相關的領域，Python 也還是那個最強的工具。本書以淺顯易懂的筆觸與大量的實例演練，引導你在動手寫程式的過程中學會 Python 的語法和程式邏輯，跨越初學者經常遇到的障礙，進入資料科學、大數據分析與人工智慧等專業的領域。有了基本的程式能力以後，便能有效的監督 AI 產生的程式碼，又或是清楚地提出自己對程式的要求。如此一來，你將能透過 vibe coding 體會到前所未有的樂趣！☛ 清楚明瞭的語法教學，第一次寫程式就上手！☛ 豐富滿點的實作範例，自己動手反覆練習最有感！☛ 無縫接軌四大套件－NumPy、matplotlib、SciPy、pandas☛ 紮穩資料科學基礎，銜接機器學習最強套件－scikit-learn☛ Requests、Beautiful Soup－網路爬蟲☛ OpenCV、YOLO－人臉辨識、物體偵測一把罩！☛ 輕鬆建立本地端 AI 助理－Ollama、Streamlit本書特色: ✯最易學習✯沒學過程式設計或學到一半就放棄的都沒關係，本書從基礎語法和程式邏輯開始，以淺顯文字及簡明程式，帶你快速學會Python在不同領域的應用。✯豐富範例✯本書提供豐富實用的範例，搭配各小節的隨堂練習和章末的學習評量，立即驗證學習成果，自學或課堂教學都適合。✯最強應用✯本書包含下列幾個與資料科學、網路爬蟲、機器學習、電腦視覺、自然語言處理、大型語言模型等應用相關的最強套件。有了這些基礎，你就可以進一步往資料科學、大數據分析、人工智慧等專業的領域發展：▪ NumPy → 資料運算▪ matplotlib → 資料視覺化▪ SciPy → 科學計算▪ pandas → 資料處理與分析▪ Requests、Beautiful Soup → 網路爬蟲▪ scikit-learn → 機器學習▪ OpenCV → 人臉偵測與辨識▪ YOLO → 物體偵測與圖像分割▪ Ollama、Streamlit → 本地端 LLM 與網頁版聊天機器人

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用Python和No-Code工具來開發專屬你的LLM應用 新手友善的LLM應用實戰指南，理解本質才能精準操作LLM這個黑盒子 從基礎AI開發開始，奠定AI應用飛躍之路 【內容簡介】 ♚學習AI開發：建立正確觀念，奠定紮實基本功 ♚理論實作並行：由淺入深學習，搭配程式碼實作 ♚套件全面剖析：理解套件背後的設計思路與取捨 ♚搭配No-Code工具：完整解析繁體中文Dify實戰 本書改編自第16屆iThome鐵人賽生成式AI組冠軍系列文章《Python新手的AI之旅：從零開始打造屬於你的AI / LLM應用》。本書將一步步帶著讀者學習建構一個AI應用的必備知識，從理論到實作都有涵蓋，不用擔心自己沒有AI的基礎。 本書專注於推論階段的LLM應用，前半部分介紹的是AI的基礎知識、LLM API的使用方法，以及圍繞在LLM周邊問題的解決方案；後半部分則詳細介紹Agent以及Dify這個No-Code LLM應用設計平台的使用方法和小訣竅；最後則是LLM應用的相關補充資料。 看完本書的你，就相當於擁有精準操作LLM這個「黑盒子」的基本能力，任何天馬行空的想法都能實現，而這也將會是你進入AI領域最開心的前奏。 【目標讀者】 ✪Python新手、想做點什麼的人。 ✪對AI有興趣、不知道怎麼開始的人。 ✪對開發LLM應用有興趣的人。 ✪不怕被說是套模仔的人。 本書改編自第16屆iThome鐵人賽生成式AI組冠軍系列文章《Python新手的AI之旅：從零開始打造屬於你的AI / LLM應用》。本書將一步步帶著讀者學習建構一個AI應用的必備知識，從理論到實作都有涵蓋，不用擔心自己沒有AI的基礎。本書專注於推論階段的LLM應用，前半部分介紹的是AI的基礎知識、LLM API的使用方法，以及圍繞在LLM周邊問題的解決方案；後半部分則詳細介紹Agent以及Dify這個No-Code LLM應用設計平台的使用方法和小訣竅；最後則是LLM應用的相關補充資料。

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使用「經濟版Copilot」輔助學習Python程式設計 VS Code + GitHub Copilot 建立你的程式閱讀力 × 提示工程力 × 架構思維 ● 不背語法，也能看懂Python程式碼 ● 9大AI提示詞，系統化訓練「程式閱讀力」 ● Copilot寫程式，你負責評估糾錯與決策 ● 從AI輔助學習到AI專案開發完整進階 ● 可與ChatGPT、Claude、Gemini搭配使用 不從背語法開始，而是先建立AI時代最重要的能力──程式閱讀力 隨著生成式AI能快速產生程式碼，「會寫程式」的定義正在轉變。在AI時代，真正的關鍵能力不再只是輸入指令，而是看懂、判斷、修正，並與AI協作完成程式設計與專案開發。 本書不是教你按快捷鍵、接受AI建議，而是從根本培養在AI時代不可或缺的核心能力——程式閱讀力。書中以新開發出的「窮人版Copilot」為核心，透過所設計出的9大AI提示詞，將「看懂程式」這件事有效轉化成結構化和系統化的程式學習方法論。 書中提供超過1000個程式範例，這些程式範例不是單純示範語法，而是學習者修煉程式閱讀力的最佳素材。每段程式碼都是一套可反覆拆解、理解與思考的「心法」，幫助你逐步建立看懂程式、評估程式與重構程式的能力。 全書依照程式學習的自然進程，分為三個修煉階段：從AI輔助學習Python，到駕馭GitHub Copilot撰寫程式，再進階到AI協作的專案開發與架構思維。所學到的不只是工具操作，更是在對的時機使用AI、評估AI的回應，以及真正掌握AI時代的程式設計能力。 你將學會 ● 使用「窮人版 Copilot」的9大提示詞看懂Python程式 ● 判斷AI產生的程式碼是否正確、可讀、可維護 ● 與GitHub Copilot協作撰寫、審查與重構程式 ● 將AI整合進版本控制、虛擬環境與專案流程 ● 建立AI時代必備的程式素養與架構思維 適合讀者 ● 想在AI時代學會程式設計的初學者 ● 已有基礎，但想突破「能寫卻寫不好」瓶頸的學習者 ● 希望導入AI輔助教學的程式設計教師與講師 本書特色 ● AI 輔助學習 × AI 輔助開發的完整整合 ● 幾乎免費的學習工具，人人都能上手 ● 超過 1000 個可反覆修煉的程式範例，建立真正的程式閱讀力

本書是以實戰應用、邁向工程師為目標的 Python 入門書，帶領讀者快速入門學會關鍵語法，再透過實作讓讀者一方面可以學以致用，實際體驗程式語言的用處；一方面在實作範例時，補足快速入門階段還沒學到的進階語法以及各式延伸套件，只要一本書即可從入門學到應用，主題涵蓋網頁應用程式、爬蟲、影像處理與辨識、大型語言模型。為了達成上述目標，本書結構安排如下：》第 1～4 章：環境建置與基本語法》第 5 章：實作檔案備份小工具》第 6,7 章：實作 YouTube 影片下載工具與影音編碼合併處理》第 8～10 章：設計網路爬蟲與 Google 試算表操作》第 11～14 章：使用 Flask 建立與部署網頁應用程式》第 15 章：學習 OpenCV 影像處理與辨識》第 16,17 章：利用 YOLO 偵測物體、肢體動作與車牌辨識》第 18 章：學習最夯的 Ollama 本地端生成式大語言模型 LLM》第 19 章：使用 Streamlit 快速開發網頁應用程式》第 20 章：用 LangChain 框架開發 RAG 應用》第 21 章：結合 LLM 設計 LINE 客服 AI 機器人實務範例選擇以應用廣泛並能跟上 AI 時代潮流為主軸。除基本語法以外，進階語法及延伸套件也不馬虎，涵蓋：》自訂類別》規則表達式》格式化字串》參數的打包與解包》with 語法》閉包與裝飾器》match...case 語法》例外處理》多執行緒》命令行參數處理》subprocess 模組》SQLite 程式庫》JSON 與 CSV 檔處理本書在撰寫風格上除了第 2 章的 Python 程式開發與 AI 輔助工具說明外，每個章節都有實例與詳細圖解，協助讀者更容易理解。在開發工具的選擇上，入門章節以方便易用的 Colab 練習基本語法，接著就以業界工程師廣為採用的 Visual Studio Code 為開發環境，並帶入 Github Copilot 工具熟悉與 AI 助理協作的流程。在設計範例時也貫徹虛擬環境的觀念，輔以多版本 Python 環境建置，避免環境污染問題，讓學習與業界接軌，學完立刻派上用場。在許多實作應用的場合，光是瞭解程式語法是不夠的，像建構網路應用程式，還需要具備網路、防火牆、資料庫系統、租用並在雲端空間部署應用程式...等，還有 AI 影像偵測及大型語言模型應用背後的類神經網路 / 深度學習