Beginning Anomaly Detection Using Python-Based Deep Learning
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This beginner-oriented book will help you understand and perform anomaly detection by learning cutting-edge machine learning and deep learning techniques. This updated second edition focuses on supervised, semi-supervised, and unsupervised approaches to anomaly detection. Over the course of the book, you will learn how to use Keras and PyTorch in practical applications. It also introduces new chapters on GANs and transformers to reflect the latest trends in deep learning. Beginning Anomaly Detection Using Python-Based Deep Learning begins with an introduction to anomaly detection, its importance, and its applications. It then covers core data science and machine learning modeling concepts before delving into traditional machine learning algorithms such as OC-SVM and Isolation Forest for anomaly detection using scikit-learn. Following this, the authors explain the essentials of machine learning and deep learning, and how to implement multilayer perceptrons for supervised anomaly detection in both Keras and PyTorch. From here, the focus shifts to the applications of deep learning models for anomaly detection, including various types of autoencoders, recurrent neural networks (via LSTM), temporal convolutional networks, and transformers, with the latter three architectures applied to time-series anomaly detection. This edition has a new chapter on GANs (Generative Adversarial Networks), as well as new material covering transformer architecture in the context of time-series anomaly detection. After completing this book, you will have a thorough understanding of anomaly detection as well as an assortment of methods to approach it in various contexts, including time-series data. Additionally, you will have gained an introduction to scikit-learn, GANs, transformers, Keras, and PyTorch, empowering you to create your own machine learning- or deep learning-based anomaly detectors. What You Will Learn Understand what anomaly detection is, why it it is important, and how it is applied Grasp the core concepts of machine learning. Master traditional machine learning approaches to anomaly detection using scikit-kearn. Understand deep learning in Python using Keras and PyTorch Process data through pandas and evaluate your model's performance using metrics like F1-score, precision, and recall Apply deep learning to supervised, semi-supervised, and unsupervised anomaly detection tasks for tabular datasets and time series applications Who This Book Is ForData scientists and machine learning engineers of all levels of experience interested in learning the basics of deep learning applications in anomaly detection.
AI影片製作工具箱 : AI繪圖合成×智慧編輯剪片×ChatGPT文案生成全攻略
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🎥 全方位視訊教學：免費又好用的「剪映」影片創作軟體，一書打通。
🎥 應用AI科技：瞭解ChatGPT、Playground AI、DALL-E等AI工具。
🎥 影片行銷指南：不僅教你製作，更指引如何於社群媒體大放異彩。
🎥 實用網路資源：為YouTuber 打造，教你如何免費下載高品質素材。
🎥 視訊特效與音訊：學習轉場、特效、文字應用與音訊的多重技巧。
🎥 互動學習方式：透過實際案例，手把手帶領你走向專業。
AI時代Math元年 : 用Python全精通矩陣及線性代數
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全書分為以下幾個部分：向量：從資料、矩陣、向量、幾何、空間開始談起，包括向量運算，範數等基本定理。接下來談到矩陣，把矩陣所有的性質(四則運算、表格、秩等)說明清楚，更有重要的內外積等。第三部分談的是向量，包括座標系、各種變換、維度、行列視，投影、正交、基等性質。第四部分談的是矩陣分解，實作了包括LU、Cholesky、QR，特徵/奇異值分解。第五部分就是談到空間的微積分，如多元函式、偏導、梯度、方向微分、泰勒展開等。也說明了拉格朗日乘子等。第六部分說明了空間幾何，包括直線、超平面、圓錐曲線等。也說明了曲面和正定性等問題。最後一部分則整理了前面所有觀念，發展至資料統計、SVD分解、機器學習、線性迴歸及PCA原理。搭配本書系其它書籍，相信AI的數學，對你來說只會是開心而不是阻礙。
AI繪圖夢工廠
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★ 最強 Midjourney、Stable Diffusion 生圖設定完全詳解
★ 超好用的 Copilot (Bing)、DALL‧E 3 輕鬆製作網路瘋傳的梗圖
★ 最高 CP 值的 AI 繪圖工具, Leonardo.Ai 讓你畫很棒又免錢
★ 打造各種寫真美少男美少女, 從 Cosplay 到時尚外拍都沒問題
★ 操作介面最簡單易懂的 Adobe Firefly，全民都能做伙來
★ AI 繪圖工具的明日之星：Tensor.Art、Krea.ai、Recraft、PixAI.art...
★ 讓 AI 化身專業攝影師, 風景人像微距商業攝影都沒問題
★ 電商業者看過來！打造自己的 Lora 模型, 讓 AI 明星免費幫你代言
★ 用 AI 幫你做室內設計, 自動生成不同風格的渲染圖
★ 誰說 AI 繪圖不識字, 教你設計風格獨具的中英文 Logo
★ 修圖、去雜物、照片上色、數位化妝, 讓 AI 變身超強 P 圖大神
★ 反覆生成都不滿意？回歸修圖老朋友 Photoshop 讓生成圖更完美
★ 用 Deforum 自動生成商業 CF 級別的酷炫短影片
★ 透過 D-ID 和 ChatGPT 讓名人開講動起來
★ AnimateDiff 讓你直接由文字生成短影片
★ 教你生成獨有風格的專屬 QRcode
★ 將生成圖片轉換成 3D 立體效果圖
★ 怪手退散！修復生成圖片的手部變形
ChatGPT 開發手冊 Turbo x Vision 進化版 : 用 OpenAI Chat/Assistants API.Function calling 設計 GPTs action.LINE/Discord bot.股市分析/自動助理
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‣ 解析實際上線的 GPTs 學會 action 開發
‣ 串接 Google 帳號認證 GPTs action 使用者身分
‣ 善用 Assistants API 設計 Discord 股票分析助理
‣ 結合 gpt-4-vision/code interpreter 設計看圖生成網頁的自動助理
‣ 使用 Assistants API 用說的就能操控 SQL 資料庫
‣ 利用 function calling 幫 LINE AI 機器人突破限制開外掛
‣ 整合 OpenAI Image API 設計 AI 文字生圖/改圖/修圖工具
‣ 詳解 OpenAI API 參數/掌握語言模型輸出變化
‣ 實作自動字幕/旁白產生器
‣ 微軟 Azure OpenAI API 差異說明, 無縫接軌轉移應用程式到 Azure 平台
本學科指引提供您資訊管理研究的資源，透過圖書館的蒐集與整理，整合館藏紙本、電子以及校外的網路資源，按資料類型排列彙編，主題式的 引介各種資源， 提供兼具廣度與深度的資料。
若您需要更進一步的協助，請與館員聯絡。
This guide directs you to resources that will best enable you to conduct management information systems research. If you need more assistance, please Ask a Librarian!
本館館藏資源以配合校內師生教學研究之需要為主，舉凡相關之圖書、期刊、多媒體資料、電子資源等均予蒐藏。
圖書/期刊 Books & Journals
電子資源 Electronic Resources
