Python數(shù)據(jù)分析與機(jī)器學(xué)習(xí)

前言 \n
\n
\n
第1章Python與數(shù)據(jù)分析 \n
\n
11概述 \n
\n
111引例 \n
\n
112數(shù)據(jù)分析與數(shù)據(jù)挖掘 \n
\n
12Python簡(jiǎn)介 \n
\n
121Python特點(diǎn) \n
\n
122Python應(yīng)用場(chǎng)合 \n
\n
13數(shù)據(jù)分析流程 \n
\n
131明確目標(biāo) \n
\n
132獲取數(shù)據(jù) \n
\n
133清洗數(shù)據(jù) \n
\n
134特征工程 \n
\n
135構(gòu)建模型 \n
\n
136模型評(píng)估 \n
\n
14數(shù)據(jù)分析庫(kù) \n
\n
141NumPy \n
\n
142Matplotlib \n
\n
143Pandas \n
\n
144Seaborn \n
\n
145Scipy \n
\n
146Sklearn \n
\n
15Python解釋器 \n
\n
151Ubuntu下安裝Python \n
\n
152Windows下安裝Python \n
\n
16Python編輯器 \n
\n
161IDLE \n
\n
162VScode \n
\n
163PyCharm \n
\n
164Anaconda \n
\n
165Jupyter \n
\n
17習(xí)題 \n
\n
第2章NumPy——數(shù)據(jù)分析基礎(chǔ) \n
工具 \n
\n
21安裝NumPy \n
\n
22ndarray對(duì)象 \n
\n
221認(rèn)識(shí)ndarray對(duì)象 \n
\n
222ndarray對(duì)象屬性 \n
\n
23創(chuàng)建ndarray對(duì)象 \n
\n
231zeros \n
\n
232ones \n
\n
233diag \n
\n
234arange \n
\n
235linspace \n
\n
236logspace \n
\n
24數(shù)組變換 \n
\n
241維度變換 \n
\n
242數(shù)組拼接 \n
\n
243數(shù)組分割 \n
\n
244數(shù)組復(fù)制 \n
\n
25索引和切片 \n
\n
26線性代數(shù) \n
\n
261矩陣運(yùn)算 \n
\n
262矩陣轉(zhuǎn)置 \n
\n
263特征根和特征向量 \n
\n
27統(tǒng)計(jì)量 \n
\n
271平均值 \n
\n
272最值 \n
\n
273中位數(shù) \n
\n
274極差 \n
\n
275方差 \n
\n
276協(xié)方差 \n
\n
277皮爾森相關(guān)系數(shù) \n
\n
28習(xí)題 \n
\n
第3章Matplotlib——數(shù)據(jù)可視化 \n
工具 \n
\n
31安裝Matplotlib \n
\n
32繪圖步驟 \n
\n
321創(chuàng)建畫(huà)布 \n
\n
322繪圖函數(shù) \n
\n
323繪圖屬性 \n
\n
33子圖基本操作 \n
\n
331pltsubplot \n
\n
332figureadd_subplot \n
\n
333pltsubplots \n
\n
34繪圖 \n
\n
341折線圖 \n
\n
342氣泡圖 \n
\n
343餅圖 \n
\n
344直方圖 \n
\n
345條形圖 \n
\n
35概率分布 \n
\n
351泊松分布 \n
\n
352正態(tài)分布 \n
\n
353均勻分布 \n
\n
354二項(xiàng)分布 \n
\n
36習(xí)題 \n
\n
第4章Pandas——數(shù)據(jù)處理工具 \n
\n
41認(rèn)識(shí)Pandas \n
\n
42Series \n
\n
421創(chuàng)建Series \n
\n
422 Series屬性 \n
\n
423訪問(wèn)Series數(shù)據(jù) \n
\n
43操作Series \n
\n
431更新Series \n
\n
432插入Series \n
\n
433刪除Series \n
\n
44DataFrame \n
\n
441創(chuàng)建DataFrame \n
\n
442DataFrame屬性 \n
\n
443選取行列數(shù)據(jù) \n
\n
45操作DataFrame \n
\n
451更新DataFrame \n
\n
452插入DataFrame \n
\n
\n
\n
453刪除DataFrame \n
\n
46Index \n
\n
461創(chuàng)建Index \n
\n
462常用屬性 \n
\n
463常用方法 \n
\n
464重建Index \n
\n
47可視化 \n
\n
471線形圖 \n
\n
472條形圖 \n
\n
473餅狀圖 \n
\n
474直方圖與密度圖 \n
\n
48數(shù)據(jù)轉(zhuǎn)換 \n
\n
481數(shù)據(jù)值替換 \n
\n
482數(shù)據(jù)映射 \n
\n
483數(shù)據(jù)值合并 \n
\n
484數(shù)據(jù)值補(bǔ)充 \n
\n
485數(shù)據(jù)離散化 \n
\n
49數(shù)據(jù)分組與聚合 \n
\n
491數(shù)據(jù)分組 \n
\n
492數(shù)據(jù)聚合 \n
\n
410讀取外部數(shù)據(jù) \n
\n
4101操作Excel \n
\n
4102操作文本文件 \n
\n
4103操作數(shù)據(jù)庫(kù) \n
\n
411習(xí)題 \n
\n
第5章Scipy——數(shù)據(jù)統(tǒng)計(jì)工具 \n
\n
51認(rèn)識(shí)Scipy \n
\n
52稀疏矩陣 \n
\n
53線性代數(shù) \n
\n
531矩陣運(yùn)算 \n
\n
532線性方程組求解 \n
\n
54數(shù)據(jù)優(yōu)化 \n
\n
541非線性方程組求解 \n
\n
542函數(shù)最值 \n
\n
543最小二乘法 \n
\n
55數(shù)據(jù)分布 \n
\n
551泊松分布 \n
\n
552正態(tài)分布 \n
\n
553均勻分布 \n
\n
554二項(xiàng)分布 \n
\n
555指數(shù)分布 \n
\n
56統(tǒng)計(jì)量 \n
\n
561眾數(shù) \n
\n
562皮爾森相關(guān)系數(shù) \n
\n
57圖像處理 \n
\n
571旋轉(zhuǎn)圖像 \n
\n
572圖像濾波 \n
\n
573邊緣檢測(cè) \n
\n
58習(xí)題 \n
\n
第6章Seaborn——數(shù)據(jù)可視化 \n
工具 \n
\n
61認(rèn)識(shí)Seaborn \n
\n
611繪圖特色 \n
\n
612圖表分類(lèi) \n
\n
613數(shù)據(jù)集 \n
\n
62繪圖設(shè)置 \n
\n
621繪圖元素 \n
\n
622主題 \n
\n
623調(diào)色板 \n
\n
63繪圖 \n
\n
631直方圖 \n
\n
632核密度圖 \n
\n
633小提琴圖 \n
\n
634分類(lèi)散點(diǎn)圖 \n
\n
635條形圖 \n
\n
636熱力圖 \n
\n
637點(diǎn)圖 \n
\n
64習(xí)題 \n
\n
第7章Sklearn——機(jī)器學(xué)習(xí)工具 \n
\n
71Sklearn簡(jiǎn)介 \n
\n
72安裝Sklearn \n
\n
73數(shù)據(jù)集 \n
\n
731小數(shù)據(jù)集 \n
\n
732大數(shù)據(jù)集 \n
\n
733生成數(shù)據(jù)集 \n
\n
74機(jī)器學(xué)習(xí)流程 \n
\n
741數(shù)據(jù)清洗 \n
\n
742劃分?jǐn)?shù)據(jù)集 \n
\n
743特征工程 \n
\n
744機(jī)器算法 \n
\n
745模型評(píng)估 \n
\n
75習(xí)題 \n
\n
\n
\n
\n
\n
第8章數(shù)據(jù)處理 \n
\n
81認(rèn)識(shí)數(shù)據(jù)處理 \n
\n
82數(shù)據(jù)清洗 \n
\n
821處理缺失值 \n
\n
822處理異常值 \n
\n
823處理重復(fù)值 \n
\n
83特征處理 \n
\n
831規(guī)范化 \n
\n
832標(biāo)準(zhǔn)化 \n
\n
833魯棒化 \n
\n
84數(shù)據(jù)分析可視庫(kù) \n
\n
841missingno庫(kù) \n
\n
842詞云 \n
\n
85案例——學(xué)生信息清洗 \n
\n
86習(xí)題 \n
\n
第9章特征工程 \n
\n
91認(rèn)識(shí)特征工程 \n
\n
92獨(dú)熱編碼 \n
\n
93特征提取 \n
\n
931DictVectorizer \n
\n
932CountVectorizer \n
\n
933TfidfVectorizer \n
\n
94中文分詞 \n
\n
941Jieba分詞庫(kù) \n
\n
942停用詞表 \n
\n
95案例——中文特征提取 \n
\n
96習(xí)題 \n
\n
第10章評(píng)價(jià)指標(biāo) \n
\n