│??├

│??│??├課時01.課程介紹（主題與大綱）.flv

│??│??├課時02.機器學習概述.flv

│??│??├課時03.使用Anaconda安裝python環境.flv

│??│??├課時04.課程數據，代碼，PPT（在參考資料界面）.swf

│??│??├課時05.科學計算庫Numpy.flv

│??│??├課時06.Numpy基礎結構.flv

│??│??├課時07.Numpy矩陣基礎.flv_d.flv

│??│??├課時08.Numpy常用函數.flv_d.flv

│??│??├課時09.矩陣常用操作.flv_d.flv

│??│??└課時10.不同復制操作對比.flv_d.flv

│??├

│??│??├課時11.Pandas數據讀取.flv

│??│??├課時12.Pandas索引與計算.flv_d.flv

│??│??├課時13.Pandas數據預處理實例.flv_d.flv

│??│??├課時14.Pandas常用預處理方法.flv_d.flv

│??│??├課時15.Pandas自定義函數.flv_d.flv

│??│??└課時16.Series結構.flv_d.flv

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│??│??├課時17.折線圖繪制.flv

│??│??├課時18.子圖操作.flv_d.flv

│??│??├課時19.條形圖與散點圖.flv_d.flv

│??│??├課時20.柱形圖與盒圖.flv_d.flv

│??│??└課時21.細節設置.flv_d.flv

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│??│??├課時22.Seaborn簡介.flv

│??│??├課時23.整體布局風格設置.flv_d.flv

│??│??├課時24.風格細節設置.flv_d.flv

│??│??├課時25.調色板.flv_d.flv

│??│??├課時26.調色板.flv_d.flv

│??│??├課時27.調色板顏色設置.flv_d.flv

│??│??├課時28.單變量分析繪圖.flv_d.flv

│??│??├課時29.回歸分析繪圖.flv_d.flv

│??│??├課時30.多變量分析繪圖.flv_d.flv

│??│??├課時31.分類屬性繪圖.flv_d.flv

│??│??├課時32.Facetgrid使用方法.flv_d.flv

│??│??└課時33.Facetgrid繪制多變量.flv_d.flv

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│??│??├課時34.熱度圖繪制.flv_d.flv

│??│??├課時35.回歸算法綜述.flv_d.flv

│??│??├課時36.回歸誤差原理推導.flv_d.flv

│??│??├課時37.回歸算法如何得出最優解.flv_d.flv

│??│??├課時38.基于公式推導完成簡易線性回歸.flv_d.flv

│??│??└課時39.邏輯回歸與梯度下降.flv_d.flv

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│??│??├課時40.使用梯度下降求解回歸問題.flv_d.flv

│??│??├課時41.決策樹算法綜述.flv_d.flv

│??│??├課時42.決策樹熵原理.flv_d.flv

│??│??├課時43.決策樹構造實例.flv_d.flv

│??│??├課時44.信息增益原理.flv_d.flv

│??│??├課時45.信息增益率的作用.flv_d.flv

│??│??├課時46.決策樹剪枝策略.flv_d.flv

│??│??└課時47.隨機森林模型.flv_d.flv

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│??│??├課時48.決策樹參數詳解.flv_d.flv

│??│??├課時49.貝葉斯算法概述.flv_d.flv

│??│??├課時50.貝葉斯推導實例.flv_d.flv

│??│??├課時51.貝葉斯拼寫糾錯實例.flv_d.flv

│??│??└課時52.垃圾郵件過濾實例.flv_d.flv

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│??│??├課時53.貝葉斯實現拼寫檢查器.flv_d.flv

│??│??├課時54.支持向量機要解決的問題.flv_d.flv

│??│??├課時55.支持向量機目標函數.flv_d.flv

│??│??├課時56.支持向量機目標函數求解.flv_d.flv

│??│??├課時57.支持向量機求解實例.flv_d.flv

│??│??├課時58.支持向量機軟間隔問題.flv_d.flv

│??│??└課時59.支持向量核變換.flv_d.flv

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│??│??├課時60.SMO算法求解支持向量機.flv_d.flv

│??│??├課時61.初識神經網絡.flv_d.flv

│??│??├課時62.計算機視覺所面臨的挑戰.flv_d.flv

│??│??├課時63.K近鄰嘗試圖像分類.flv_d.flv

│??│??├課時64.超參數的作用.flv_d.flv

│??│??├課時65.線性分類原理.flv_d.flv

│??│??├課時66.神經網絡-損失函數.flv_d.flv

│??│??├課時67.神經網絡-正則化懲罰項.flv_d.flv

│??│??├課時68.神經網絡-softmax分類器.flv_d.flv

│??│??├課時69.神經網絡-最優化形象解讀.flv_d.flv

│??│??├課時70.神經網絡-梯度下降細節問題.flv_d.flv

│??│??├課時71.神經網絡-反向傳播.flv_d.flv

│??│??├課時72.神經網絡架構.flv_d.flv

│??│??├課時73.神經網絡實例演示.flv_d.flv

│??│??└課時74.神經網絡過擬合解決方案.flv_d.flv

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│??│??├課時75.感受神經網絡的強大.flv_d.flv

│??│??├課時76.集成算法思想.flv_d.flv

│??│??├課時77.xgboost基本原理.flv_d.flv

│??│??├課時78.xgboost目標函數推導.flv_d.flv

│??│??├課時79.xgboost求解實例.flv_d.flv

│??│??├課時80.xgboost安裝.flv_d.flv

│??│??└課時81.xgboost實戰演示.flv_d.flv

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│??│??├課時82.Adaboost算法概述.flv_d.flv

│??│??├課時83.自然語言處理與深度學習加微信ff1318860.flv_d.flv

│??│??├課時84.語言模型.flv_d.flv

│??│??├課時85.-N-gram模型.flv_d.flv

│??│??├課時86.詞向量.flv_d.flv

│??│??├課時87.神經網絡模型.flv_d.flv

│??│??├課時88.Hierarchical.Softmax.flv_d.flv

│??│??├課時89.CBOW模型實例.flv_d.flv

│??│??├課時90.CBOW求解目標.flv_d.flv

│??│??└課時91.梯度上升求解.flv_d.flv

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│??│??├課時92.負采樣模型.flv_d.flv

│??│??├課時93.無監督聚類問題.flv_d.flv

│??│??├課時94.聚類結果與離群點分析.flv_d.flv

│??│??├課時95.K-means聚類案例對NBA球員進行評估.flv_d.flv

│??│??├課時96.使用Kmeans進行圖像壓縮.flv_d.flv

│??│??└課時97.K近鄰算法原理.flv_d.flv

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│??│??├課時100.PCA實例.flv_d.flv

│??│??├課時101.SVD奇異值分解原理.flv_d.flv

│??│??├課時98.K近鄰算法代碼實現.flv_d.flv

│??│??└課時99.PCA基本原理.flv_d.flv

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│??│??├課時102.SVD推薦系統應用實例.flv_d.flv

│??│??├課時103.使用python庫分析汽車油耗效率.flv

│??│??├課時104.使用scikit-learn庫建立回歸模型.flv_d.flv

│??│??├課時105.使用邏輯回歸改進模型效果.flv_d.flv

│??│??├課時106..模型效果衡量標準.flv_d.flv

│??│??├課時107.ROC指標與測試集的價值.flv_d.flv

│??│??└課時108.交叉驗證.flv_d.flv

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│??│??├課時109.多類別問題.flv_d.flv

│??│??├課時110.Kobe.Bryan生涯數據讀取與簡介.flv

│??│??├課時111.特征數據可視化展示.flv_d.flv

│??│??└課時112.數據預處理.flv_d.flv

│??├

│??│??├課時113.使用Scikit-learn建立模型.flv_d.flv

│??│??├課時114.船員數據分析.flv

│??│??├課時115.數據預處理.flv_d.flv

│??│??├課時116.使用回歸算法進行預測.flv_d.flv

│??│??└課時117.使用隨機森林改進模型.flv_d.flv

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│??│??├課時118.隨機森林特征重要性分析.flv_d.flv

│??│??├課時119.案例背景和目標.flv_d.flv

│??│??├課時120.樣本不均衡解決方案.flv_d.flv

│??│??├課時121.下采樣策略.flv_d.flv

│??│??├課時122.交叉驗證.flv_d.flv

│??│??├課時123.模型評估方法.flv_d.flv

│??│??├課時124.正則化懲罰.flv_d.flv

│??│??├課時125.邏輯回歸模型.flv_d.flv

│??│??├課時126.混淆矩陣.flv_d.flv

│??│??└課時127.邏輯回歸閾值對結果的影響.flv_d.flv

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│??│??├課時128.SMOTE樣本生成策略.flv_d.flv

│??│??├課時129.文本分析與關鍵詞提取.flv_d.flv

│??│??├課時130.相似度計算.flv_d.flv

│??│??├課時131.新聞數據與任務簡介.flv_d.flv

│??│??├課時132.TF-IDF關鍵詞提取.flv_d.flv

│??│??└課時133.LDA建模.flv_d.flv

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│??│??├課時134.基于貝葉斯算法進行新聞分類.flv_d.flv

│??│??├課時135.章節簡介.flv

│??│??├課時136.Pandas生成時間序列.flv_d.flv

│??│??├課時137.Pandas數據重采樣.flv_d.flv

│??│??├課時138.Pandas滑動窗口.flv_d.flv

│??│??├課時139.數據平穩性與差分法.flv_d.flv

│??│??├課時140.ARIMA模型.flv_d.flv

│??│??├課時141.相關函數評估方法.flv_d.flv

│??│??├課時142.建立ARIMA模型.flv_d.flv

│??│??├課時143.參數選擇.flv_d.flv

│??│??├課時144.股票預測案例.flv_d.flv

│??│??└課時145.使用tsfresh庫進行分類任務.flv_d.flv

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│??│??├課時146.維基百科詞條EDA.flv_d.flv

│??│??├課時147.使用Gensim庫構造詞向量.flv_d.flv

│??│??├課時148.維基百科中文數據處理.flv_d.flv

│??│??└課時149.Gensim構造word2vec模型.flv_d.flv

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│??│??├課時150.測試模型相似度結果.flv_d.flv

│??│??├課時151.數據清洗過濾無用特征.flv_d.flv

│??│??├課時152.數據預處理.flv_d.flv

│??│??└課時153.獲得最大利潤的條件與做法.flv_d.flv

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│??│??├課時154.預測結果并解決樣本不均衡問題.flv_d.flv

│??│??├課時155.數據背景介紹.flv_d.flv

│??│??├課時156.數據預處理.flv_d.flv

│??│??├課時157.嘗試多種分類器效果.flv_d.flv

│??│??└課時158.結果衡量指標的意義.flv_d.flv

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│??│??├課時159.應用閾值得出結果.flv_d.flv

│??│??├課時160.內容簡介.flv_d.flv

│??│??├課時161.數據背景介紹.flv

│??│??├課時162.數據讀取與預處理.flv_d.flv

│??│??├課時163.數據切分模塊.flv_d.flv

│??│??├課時164.缺失值可視化分析.flv_d.flv

│??│??├課時165.特征可視化展示.flv_d.flv

│??│??├課時166.多特征之間關系分析.flv_d.flv

│??│??└課時167.報表可視化分析.flv_d.flv

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│??│??├課時168.紅牌和膚色的關系.flv_d.flv

│??│??├課時169.數據背景簡介.flv_d.flv

│??│??├課時170.數據切片分析.flv_d.flv

│??│??├課時171.單變量分析.flv_d.flv

│??│??├課時172.峰度與偏度.flv_d.flv

│??│??├課時173.數據對數變換.flv_d.flv

│??│??└課時174.數據分析維度.flv_d.flv

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│??│??├課時175.變量關系可視化展示.flv_d.flv

│??│??├課時176.建立特征工程.flv_d.flv

│??│??├課時177.特征數據預處理.flv_d.flv

│??│??└課時178.應用聚類算法得出異常IP點.flv_d.flv