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ai 必須!從做中學貝氏統計:從事機器學習、深度學習、資料科學、大數據分析一定要懂的統計利器: 因為您查詢了關鍵字: 深度學習,推薦您可能感興趣的商品
越來越多工具的開發,也降低了學習的門檻,許多沒有資料科學相關背景的學習者,也可以透過Keras和TensorFlow等先進工具,快速建構有趣的深度學習應用。 本書內容由淺入深,不只對PyTorch進行系統化的介紹,也詳細說明瞭神經網路、CNN網路、RNN網路及強化學習等主題。 本書還安排了18個實習,以PyTorch實作深度學習的各種演算法,經由實作的過程,可有效幫助讀者學習,進入深度學習的世界。
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ai 必須!從做中學貝氏統計:從事機器學習、深度學習、資料科學、大數據分析一定要懂的統計利器: 《度度鳥》AI 必須!從做中學貝氏統計-從事機器學習、深度學習、資料科學、大│博碩文化│Therese│定價:1200元
深度學習是人工智慧的一個分支,相較於傳統的機器學習,深度學習在某些領域中更接近人類智慧,而逐漸走進我們的生活中,常見的應用如人臉辨識、語音識別、智慧駕駛等。 ai 必須!從做中學貝氏統計:從事機器學習、深度學習、資料科學、大數據分析一定要懂的統計利器2025 黃駿 國立臺灣大學腦與心智科學研究所碩士班畢業後,曾擔任過行銷、產品設計等工作。 國立臺灣大學腦與心智科學研究所碩士班畢業後,曾擔任過行銷、產品設計等工作。 若您要辦理退貨,請先透過PChome ai 必須!從做中學貝氏統計:從事機器學習、深度學習、資料科學、大數據分析一定要懂的統計利器 24h購物客服系統填寫退訂單,我們將於接獲申請之次日起1個工作天內檢視您的退貨要求,檢視完畢後將以E-mail回覆通知您,並將委託本公司指定之宅配公司,在5個工作天內透過電話與您連絡前往取回退貨商品。 請您保持電話暢通,並備妥原商品及所有包裝及附件,以便於交付予本公司指定之宅配公司取回(宅配公司僅負責收件,退貨商品仍由特約廠商進行驗收),宅配公司取件後會提供簽收單據給您,請注意留存。
因為公司的預先統計表明該公司的僱員中有0.5%的人吸食毒品,所以這個值就是D的事前機率。 \r\n\r\n\r\n\r\n接受付款方式 \r\n全面改成輕鬆付付款\r\n\r\n收款期限 \r\n不論現貨or預購書籍得標後請於五天內完成匯款,若有特殊原因滙款有延誤的話,請來信或者評價告知我們,以便我們保留你的商品。 逾期未付款且不主動連絡者加黑名單,並且給予負評價 \r\n\r\n交貨方式 \r\n買方付運費.
ai 必須!從做中學貝氏統計:從事機器學習、深度學習、資料科學、大數據分析一定要懂的統計利器: Python 爬蟲入門特訓 ─ 資料抓取與處理應用
柏南克以全新的觀點,娓娓向讀者說明聯準會的運作及背後邏輯。 他指出經濟的改變如何推動聯準會的創新,也列出聯準會面臨的新挑戰,包括通膨再現、加密貨幣、金融不穩定的風險增加,及聯準會的獨立性所受到的威脅。 財團法人人工智慧科技基金會(AIF)深化產官學與跨產業的經驗資源連結,以人工智慧做為切入點,協助產業培育人才、掌握關鍵技術,並進一步落實到企業應用端,創造新的商機與價值。
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” width=”605px” alt=”ai 必須!從做中學貝氏統計:從事機器學習、深度學習、資料科學、大數據分析一定要懂的統計利器”/>
Q2:我本身並沒有產品和服務,也沒什麼實務上的經驗,那又能如何賺錢呢? A:我們這個課程共有11項贈品,其中第2項贈品便是資訊產品創造藍圖,它將教您如何用最簡潔而快速的方法創出屬於您自己的資訊產品。 一般的課程大多是教您如何捕魚,但多數的成功緻富者,其成功的關鍵卻不是仰賴捕魚技術,而是仰賴借力之術,因為唯有借力才能無中生有! 本課程3天共有三套樣版,其中一套樣版便是教您打造在沒有任何商品與服務,也沒有任何資源的情況下,就能快速借力致富的樣版! 本課程二位講師都是白手起家,對於沒有實務經驗的新手會格外用心,請放心。
ai 必須!從做中學貝氏統計:從事機器學習、深度學習、資料科學、大數據分析一定要懂的統計利器: 電腦/平板/週邊
● 創造資訊型產品計劃書 ● 15個步驟建立你的資訊型產品事業 ● E-mail精準行銷的10個法則 ● 10個別人沒有告訴你的有效文案撰寫法則 Q5:請問贈品中自動財富系統 6片DVD是什麼? 內容為《借力淘金!最吸利的鈔級魚池賺錢術》作者之一王紫傑所錄製的DVD,內容為有關網路行銷的知識和技巧,非常豐富且實用,免費送給您。 然後就進入機器學習的重頭戲,從資料前處理到迴歸、分類模型的建立,以及當數據的特徵數過多時的 PCA、LDA 統計降維法。 從類神經網路開始進入深度學習的範疇,包括前向傳遞、梯度下降法與倒傳遞學習法的手算實作,幫助讀者一步步建立深度學習的演算邏輯,並利用參數常規化解決模型過擬合 (over-fitting) 的問題。 最後,導入模型評估,例如二元、多元分類模型評估指標、迴歸模型評估指標、4 種交叉驗證的方法,做為判斷模型好壞的參考依據。
- 她致力於開發統計方法與應用以推動公共衛生與自然資源事務。
- 國立臺灣大學腦與心智科學研究所碩士班畢業後,曾擔任過行銷、產品設計等工作。
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- 取決於不同的分解形式,可以證明某些積分必為1,因此分解形式可被簡化。
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- 為了節省您的時間,本列表整理每個書籍重點資訊,讓您可以快速瀏覽這文章所提供的書籍是否是您所需要的,點選您有興趣產品的「名稱」或「圖示」可以進一步跳到文章所屬的介紹區塊瞭解更多細節。
- 本書是一本紀實作品,作者特里普‧米克爾以其過去五年的第一手報導為基礎,其中包括為《華爾街日報》報導蘋果公司的四年。
AIF透過文章分享基金會最新消息及技術新知,期待為臺灣產業注入科技能量。 ai 必須!從做中學貝氏統計:從事機器學習、深度學習、資料科學、大數據分析一定要懂的統計利器 辦理退換貨時,商品必須是全新狀態與完整包裝(請注意保持商品本體、配件、贈品、保證書、原廠包裝及所有附隨文件或資料的完整性,切勿缺漏任何配件或損毀原廠外盒)。 退回商品無法回復原狀者,恐將影響退貨權益或需負擔部分費用。 P代表僱員吸毒的機率,不考慮其他情況,該值為0.005。
ai 必須!從做中學貝氏統計:從事機器學習、深度學習、資料科學、大數據分析一定要懂的統計利器: 相關文章
如因合作廠商無法提供商品或服務,請與本公司聯繫辦理退貨或換成等值商品。 運送及其他說明 商品退貨需知 關於退貨: PChome 24h購物的消費者,都可以依照消費者保護法的規定,享有商品貨到日起七天猶豫期的權益。 但猶豫期並非試用期,所以,您所退回的商品必須是全新的狀態、而且完整包裝;請注意保持商品本體、配件、贈品、保證書、原廠包裝及所有附隨文件或資料的完整性,切勿缺漏任何配件或損毀原廠外盒。 數學、統計與科學都是理性、客觀、精確的代表,但也是資訊時代更容易操弄人心的騙術,而且更難被識破! ai 必須!從做中學貝氏統計:從事機器學習、深度學習、資料科學、大數據分析一定要懂的統計利器 統計、圖表、懶人包,常是理性裝扮的鬼扯,點贊、分享、演算法,助長類事實瘋傳成禍,數據識讀可說是深度偽造時代最重要的思辨素養。 PyTorch是一個開源的Python深度學習函式庫,這個軟體主要由Facebook的人工智慧研究團隊開發,而由於PyTorch的語法簡單,且擁有完善的文件說明,目前已成為開發深度學習的主要框架之一。
- PyTorch是一個開源的Python深度學習函式庫,這個軟體主要由Facebook的人工智慧研究團隊開發,而由於PyTorch的語法簡單,且擁有完善的文件說明,目前已成為開發深度學習的主要框架之一。
- 思考未來的首要之務是掌握現況,但我們發現即使是老師、投資銀行家和諾貝爾獎得主這些具備專業知識的人員,對於世界都可能有很多誤解,全球公衛學家和公共教育家漢斯.
- 貝氏公式的一個用途,即透過已知的三個機率而推出第四個機率。
- 本課程3天共有三套樣版,其中一套樣版便是教您打造在沒有任何商品與服務,也沒有任何資源的情況下,就能快速借力致富的樣版!
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為適應當前教育教學改革的要求,更進一步地踐行人工智慧模型與演算法應用,作者以實踐教學與創新能力培養為目標,採取了創新方式,從不同難度、不同類型、不同演算法融合。 Python作為人工智慧和巨量資料的主要開發語言,具有靈活性強、擴充性好、應用面廣、可移植、可擴充、可嵌入等特點,近幾年發展迅速,熱度上漲,人才需求量逐年攀升,相關課程已經成為大專院校的專業課程。 北京郵電大學教授,擁有超過10年的軟硬體開發經驗,長期致力於物聯網、雲端運算與人工智慧的研究工作。 在教學中以興趣為導向,激發學生的創造性;以素質為基礎,提高自身教學水平;以科研為手段,促進教學理念的轉變。 在教學與科研實踐中指導學生實現300餘個創新案例,主持30餘項課題的研究工作,在國內外學術期刊及會議發表論文100餘篇,申請專利50餘項,出版圖書20餘部。
ai 必須!從做中學貝氏統計:從事機器學習、深度學習、資料科學、大數據分析一定要懂的統計利器: 推薦品牌
然而,這兩者是有確定的關係的,貝氏定理就是這種關係的陳述。 貝氏公式的一個用途,即透過已知的三個機率而推出第四個機率。 如您收到商品,請依正常程序儘速檢查商品,若商品發生新品瑕疵之情形,您可申請更換新品或退貨,請直接點選聯絡我們。 依照客戶指定配送之商品(約配商品)接獲訂單逾30日您未通知出貨及受領商品,為了保障您的權益,本公司得取消訂單,請客戶重新下單購買。 個人衛生用品除商品本身有瑕疵外,未拆封商品仍享有十天猶豫期之退貨權利。
貝氏網路為此方法的一個例子,貝氏網路指定數個變數的聯合機率分佈的分解型式,該機率分佈滿足下述條件:當其他變數的條件機率給定時,該變數的條件機率為一簡單型式。 在神經網路的世界中,NLP(自然語言處裡)已逐漸成為AI領域中的主流! 因此在IT抑或是各大產業有愈來愈多的人投入在文字與語音的研究中,有愈來愈多的資訊系統應用與產品出現在現代人類的生活中,產生十分巨大的影響。 LINE 購物是匯集購物情報與商品資訊的整合性平臺,商品資料更新會有時間差,請務必點擊商品至各合作網路商家,確認現售價與購物條件,一切資訊以合作廠商網頁為準。 本公司對於所販售具遞延性之商品或服務,消費者權益均受保障。
ai 必須!從做中學貝氏統計:從事機器學習、深度學習、資料科學、大數據分析一定要懂的統計利器: 商品描述
當然本書不可能把完整的統計學全都搬進來,此處只介紹機器學習、深度學習需要用到的統計基礎知識,縮短您的學習時間。 不過,大部分電腦相關科系出身的人並不熟悉統計學,因此在更上一層樓的時候容易遇到障礙。 有鑒於此,小編在推出《機器學習的數學基礎》(天瓏專業書店年度暢銷第一名) 一書之後,就積極開發 AI 與統計學相關的書籍。 在尋尋覓覓之後請到擅長統計與機器學習的黃志勝博士出馬撰寫《機器學習的統計基礎》,首要之務就是讓讀者不要視統計為畏途,因此在書中設計大量範例以降低學習難度,務求讀得懂、做得出來才容易吸收,進而搭好統計與機器學習的橋樑。
ai 必須!從做中學貝氏統計:從事機器學習、深度學習、資料科學、大數據分析一定要懂的統計利器: Python 資料科學實戰教本:爬蟲、清理、資料庫、視覺化、探索式分析、機器學習建模,數據工程一次搞定!
若要辦理退貨,請在商品鑑賞期內寄回,且商品必須是全新狀態與完整包裝(商品、附件、發票、隨貨贈品等)否則恕不接受退貨。 由於作者經驗與水準有限,書中難免存在疏漏及不當之處,衷心地希望各位讀者多提寶貴意見及具體整改措施,以便作者進一步修改和完善。 通常,事件A在事件B已發生的條件下發生的機率,與事件B在事件A已發生的條件下發生的機率是不一樣的。