統計分析

手把手打開 Python 資料分析大門已額滿

手把手打開 Python 資料分析大門

資料科學是現在熱門的領域,而 Python 是資料分析的當紅程式語言。然而很多 Python 資料分析主要套件並不全然那麼直覺,使得不少人學了基本語法之後,一直無法進入資料分析的領域。這個讓你掌握 Python 資料分析重要套件,如 NumPy, Matplotlib, Pandas, SciKit Learn 等等主要的功能與概念。
講者以多年教授 Python 的經驗,幫你破除容易卡關的地方。更重要的是,我們學習到的不只是這些套件的語法,而是瞭解整個資料分析的概念。在本課程之後,可以更深入的學習統計分析、機器學習乃至深度學習。
本次演講內容可分為四個部分:
  1. 用 Jupyter Notebook 打造資料分析的試練場 * Jupyter Notebook 互動功能 * NumPy 陣列導向程式設計
  2. 數據清理和視覺化 * Pandas 整理數據資料 * Matplolib 做資料視覺化
  3. 用線性回歸做預測 * 資料科學的基本概念 * 線性回歸實作
  4. 使用 SciKit Learn 做機器學習 * 監督式學習範例 -- SVM * 非監督式學習範例 -- K-Means
 

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統計學家教你穩紮穩打 R 語言資料分析已額滿

統計學家教你穩紮穩打 R 語言資料分析

資料科學是綜合統計學、資訊科學及領域知識的一門新興學科。因此,要成為一名資料科學家,對統計當然要有基本的認識。舉凡日常的機率統計問題,例如:算機率值,統計參數估計,假設檢定及模型配適等等,除了需要理論証明推導之外,也需以程式做數值的模擬與驗証。而 R 語言正是研究者分析資料及執行統計模擬不可或缺的工具。也因為 R 軟體具有豐富的統計套件,也成為資料科學領域裡最受歡迎的程式語言之一。本課程由統計學家教您用 R 進行資料處理、呈現及統計分析。從第一天 R 的基礎 + 進階 (資料輸出輸入及處理、統計圖形、機率分佈、假設檢定、變異數分析、模擬統計模型與迴歸分析) 到第二天的統計分析方法應用(探索式資料分析、資料探勘案例研究),除了著重在方法理論的講述、假設及觀念的闡釋,同時也強調實際 R 程式撰寫操作,希望藉由本課程之訓練,奠定學員 R 程式撰寫及資料統計分析的基礎,並具有判斷不同狀況該用什麼不同的統計方法的數據能力。  

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給工程師的統計學及資料分析 123已額滿

給工程師的統計學及資料分析 123

「統計學」,是一個大家都熟悉卻可能又陌生的名詞。做為傳統上最接近資料科學、藉由分析資料去探索事實真相的一門學問,統計學遍佈在大專院校的各個系所中,在以往是許多學生最大的惡夢之一,現在卻又在大數據的時代,被許多人宣稱統計學已死。到底什麼是統計學?統計學包含資料分析,還是資料分析包含統計學?統計學能做到什麼,又不能做到什麼?會算平均數跟標準差之後,如果懂機率學,還能多做些什麼?這門課程將由臺大資管系孔令傑助理教授主講,用一天的時間對統計學與資料分析做一個入門的介紹。時間雖短,內容雖淺,相信仍可以幫大家釐清一些概念,也讓初學者學到一些可以實戰的技術。更重要的是,這門課希望能給大家在未來繼續學習進階知識的動機與基礎。本課程由四個部分組成:
  1. 總是抽不到大獎的抽樣分佈 課程將從基本的母體與樣本概念以及資料測量尺度出發,接著切入統計學的科學核心基礎:抽樣分佈。在用樣本資料對母體做一些猜想之前,先瞭解一下隨機樣本的機率性質吧!
  2. 假設檢定與一點都不神秘的 p 值 我們將介紹統計學的核心觀念「假設檢定」,也就是如何對未知的母體建立假說、如何以樣本資料同意或推翻假說,以及最重要地,如何估計自己的結論犯錯的機率。我們也會介紹在假設檢定中扮演關鍵角色的「p 值」,它如何被使用、又如何被誤用。
  3. 沒什麼學問的迴歸分析 當你想知道一堆變數如何合起來影響一個變數時,迴歸分析是你最好的朋友 (之一)。我們將介紹迴歸分析的基本原理、模型的解釋力與意涵、如何一股腦地把所有變數都丟進迴歸模型,以及這樣做有什麼好處跟壞處。
  4. 大有學問的迴歸分析 延續上一個模組,我們探討迴歸分析的各種變化,協助你釐清變數間錯綜複雜的關係。雖然不能讓你一秒變專家,但是可以讓你一秒看起來像專家,有時候還可以一秒戳破看起來像專家的人的錯誤。
除了介紹概念,我們也介紹如何在 R 語言中實作課程裡提到的統計方法,並且在現場讓大家動手實作。

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統計學家教你穩紮穩打 R 語言資料分析已額滿

統計學家教你穩紮穩打 R 語言資料分析

資料科學是綜合統計學、資訊科學及領域知識的一門新興學科。因此,要成為一名資料科學家,對統計當然要有基本的認識。舉凡日常的機率統計問題,例如:算機率值,統計參數估計,假設檢定及模型配適等等,除了需要理論証明推導之外,也需以程式做數值的模擬與驗証。而 R 語言正是研究者分析資料及執行統計模擬不可或缺的工具。也因為 R 軟體具有豐富的統計套件,也成為資料科學領域裡最受歡迎的程式語言之一。本課程由統計學家教您用 R 進行資料處理、呈現及統計分析。從第一天 R 的基礎 + 進階 (資料輸出輸入及處理、統計圖形、機率分佈、假設檢定、變異數分析、模擬統計模型與迴歸分析) 到第二天的統計分析方法應用(探索式資料分析、資料探勘案例研究),除了著重在方法理論的講述、假設及觀念的闡釋,同時也強調實際 R 程式撰寫操作,希望藉由本課程之訓練,奠定學員 R 程式撰寫及資料統計分析的基礎,並具有判斷不同狀況該用什麼不同的統計方法的數據能力。  

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統計學家教你穩紮穩打 R 語言資料分析已額滿

統計學家教你穩紮穩打 R 語言資料分析

統計學家教你穩紮穩打 R 語言資料分析資料科學是綜合統計學、資訊科學及領域知識的一門新興學科。因此,要成為一名資料科學家,對統計當然要有基本的認識。舉凡日常的機率統計問題,例如:算機率值,統計參數估計,假設檢定及模型配適等等,除了需要理論証明推導之外,也需以程式做數值的模擬與驗証。而 R 語言正是研究者分析資料及執行統計模擬不可或缺的工具。也因為 R 軟體具有豐富的統計套件,也成為資料科學領域裡最受歡迎的程式語言之一。本課程由統計學家教您用 R 進行資料處理、呈現及統計分析。從第一天 R 的基礎 + 進階 (資料輸出輸入及處理、統計圖形、機率分佈、假設檢定、變異數分析、模擬統計模型與迴歸分析) 到第二天的統計分析方法應用(探索式資料分析、資料探勘案例研究),除了著重在方法理論的講述、假設及觀念的闡釋,同時也強調實際 R 程式撰寫操作,希望藉由本課程之訓練,奠定學員 R 程式撰寫及資料統計分析的基礎,並具有判斷不同狀況該用什麼不同的統計方法的數據能力。 

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人類行為大數據分析:資料科學如何應用在教育及醫療領域已額滿

人類行為大數據分析:資料科學如何應用在教育及醫療領域

人類本身具有透過觀察另一人的行為以做出高階層判斷,如情緒、個性、喜好、意圖…等訊息的高度整合能力。這種人類的主觀感知機制不僅發生在日常生活中,更早已廣泛在行為科學 (behavior science) 領域中被應用於專業主觀評量與行為分析。近年來,隨著工程訊號處理演算法的進步,學科領域界線的破除,加上大數據資料科學的發展,慢慢匯流出新興跨學科整合式「人類行為訊號處理」:建置高可信度 (reliability)、可複製性 (repeatable) 及可擴展性 (scalable) 的系統將此人類的主觀感知機制自動化。 本課程將以數個教育及醫療應用實例為主軸,包含教育演講自動評分建置、急診檢傷疼痛指數系統開發、至臨床自閉症類群症狀行為診斷分析等等,貫穿並拆解「人類行為訊號處理」四大簡易步驟。希望透過本課程提供的簡易上手指南後,學員可以開始將各自領域手邊目前依人類的「主觀」認知而形成的專業判斷依據納入全新以資料角度而產生的「客觀」人類行為分析之決策工具。
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給工程師的統計學及資料分析 123已額滿

給工程師的統計學及資料分析 123

「統計學」,是一個大家都熟悉卻可能又陌生的名詞。做為傳統上最接近資料科學、藉由分析資料去探索事實真相的一門學問,統計學遍佈在大專院校的各個系所中,在以往是許多學生最大的惡夢之一,現在卻又在大數據的時代,被許多人宣稱統計學已死。到底什麼是統計學?統計學包含資料分析,還是資料分析包含統計學?統計學能做到什麼,又不能做到什麼?會算平均數跟標準差之後,如果懂機率學,還能多做些什麼? 這門課程將由臺大資管系孔令傑助理教授主講,用一天的時間對統計學與資料分析做一個入門的介紹。時間雖短,內容雖淺,相信仍可以幫大家釐清一些概念,也讓初學者學到一些可以實戰的技術。更重要的是,這門課希望能給大家在未來繼續學習進階知識的動機與基礎。
課程介紹
手把手教你 R 語言資料分析實務已額滿

手把手教你 R 語言資料分析實務

在此課程中將帶領對資料分析感到陌生卻又充滿興趣的您,完整地學會運用 R 語言從最初的蒐集資料、探索性分析解讀資料,並進行文字探勘,發現那些肉眼看不見、隱藏在資料底下的意義。此課程主要設計給對於 R 語言有基本認識,想要進一步熟悉實作分析的朋友們,希望在課程結束後,您能夠更熟悉 R 語言這個豐富的分析工具。透過蘋果日報慈善捐款的資料集,了解如何從頭解析網頁,撰寫爬蟲自動化收集資訊;取得資料後,能夠靈活處理資料,做清洗、整合及探索;並利用現成的套件進行文字探勘、文本解析;我們將一步步實際走一回資料分析的歷程,處理、觀察、解構資料,試著看看人們在捐款的決策過程中,究竟是什麼因素產生了影響,以及這些結果又是如何從資料中挖掘而出的呢?

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星火燎原 - Spark 機器學習初探已額滿

星火燎原 - Spark 機器學習初探

此課程專為 Spark 入門者設計,在六小時帶您從無到有建置 Spark 開發環境,並以實作方式帶領您了解 Spark 機器學習函式庫 (MLlib) 的應用及開發。課程實作將以 Spark 核心之實作語言 - Scala 為主,搭配 Scala IDE eclipse 及相關 Library 建置本機開發環境,透過 IDE 強大的開發及偵錯功能加速開發流程;並介紹如何佈置至 Spark 平台,透過 Spark-submit 執行資料分析工作。
本課程涵蓋機器學習中最常使用之分類、迴歸及分群方法,在本課程中您將會了解到如何操作 Spark 核心資料集 - Resilient Distributed Dataset (RDD) 取得資料的概括統計量 (summary statistics);並了解決策樹演算法 (Decision Tree)、最小平方法 (Linear least squares) 及 K-Means 演算法如何應用於租借量分析預測及網頁分類等情境。
歡迎對 Spark 感興趣,卻不知從何下手;或想快速的對 Spark 機器學習有初步的了解的您參與!
課程介紹
手把手教你 R 語言資料分析實務已額滿

手把手教你 R 語言資料分析實務

在此課程中將帶領對資料分析感到陌生卻又充滿興趣的您,完整地學會運用 R 語言從最初的蒐集資料、探索性分析解讀資料,並進行文字探勘,發現那些肉眼看不見、隱藏在資料底下的意義。此課程主要設計給對於 R 語言有基本認識,想要進一步熟悉實作分析的朋友們,希望在課程結束後,您能夠更熟悉 R 語言這個豐富的分析工具。透過蘋果日報慈善捐款的資料集,了解如何從頭解析網頁、熟悉 xpath 語法,撰寫爬蟲自動化收集資訊;取得資料後,能夠靈活處理資料,做清洗、整合及探索;並利用現成的套件進行文字探勘、文本解析;我們將一步步實際走一回資料分析的歷程,處理、觀察、解構資料,試著看看人們在捐款的決策過程中,究竟是什麼因素產生了影響,以及這些結果又是如何從資料中挖掘而出的呢?

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