课程名称
10套 国外顶级 数据分析视频 全英文 带字幕 带笔记 高大上,资源教程下载
课程目录
047_Model Thinking_模型思维\
data analysis and statistical inference\
Data Visualization\
Dino 101 Dinosaur Paleobiology\
Getting and Cleaning Data\
Mining Massive Datasets\
Model Thinking _ Scott Page\
modelthinkingzh-001\
R Programming\
Stanford Statistical Learning 2014\
The Data Scientist’s Toolbox\
详细目录:
├─047_Model Thinking_模型思维
│ ├─Model Thinking
│ │ 1 – 1 – Why Model (853).mp4
│ │ 1 – 2 – Intelligent Citizens of the World (1131).mp4
│ │ 1 – 3 – Thinking More Clearly (1050).mp4
│ │ 1 – 4 – Using and Understanding Data (1014).mp4
│ │ 1 – 5 – Using Models to Decide Strategize and Design (1526).mp4
│ │ 10 – 1 – Markov Models (426).mp4
│ │ 10 – 2 – A Simple Markov Model (1127).mp4
│ │ 10 – 3 – Markov Model of Democratization (821).mp4
│ │ 10 – 4 – Markov Convergence Theorem (1033).mp4
│ │ 10 – 5 – Exapting the Markov Model (1011).mp4
│ │ 11 – 1 – Lyapunov Functions (913).mp4
│ │ 11 – 2 – The Organization of Cities (1214).mp4
│ │ 11 – 3 – Exchange Economies and Externalities (918).mp4
│ │ 11 – 4 – Time to Convergence and Optimality (804).mp4
│ │ 11 – 5 – Lyapunov Fun and Deep (840).mp4
│ │ 11 – 6 – Lyapunov or Markov (724).mp4
│ │ 12 – 1 – Coordination and Culture (337).mp4
│ │ 12 – 2 – What Is Culture And Why Do We Care (1543).mp4
│ │ 12 – 3 – Pure Coordination Game (1348).mp4
│ │ 12 – 4 – Emergence of Culture (1101).mp4
│ │ 12 – 5 – Coordination and Consistency (1703).mp4
│ │ 13 – 1 – Path Dependence (723).mp4
│ │ 13 – 2 – Urn Models (1626).mp4
│ │ 13 – 3 – Mathematics on Urn Models (1446).mp4
│ │ 13 – 4 – Path Dependence and Chaos (1108).mp4
│ │ 13 – 5 – Path Dependence and Increasing Returns (1231).mp4
│ │ 13 – 6 – Path Dependent or Tipping Point (952).mp4
│ │ 14 – 1 – Networks (704).mp4
│ │ 14 – 2 – The Structure of Networks (1930).mp4
│ │ 14 – 3 – The Logic of Network Formation (1003).mp4
│ │ 14 – 4 – Network Function (1310).mp4
│ │ 15 – 1 – Randomness and Random Walk Models (305).mp4
│ │ 15 – 2 – Sources of Randomness (515).mp4
│ │ 15 – 3 – Skill and Luck (828).mp4
│ │ 15 – 4 – Random Walks (1229).mp4
│ │ 15 – 5 – Random Walks and Wall Street (751).mp4
│ │ 15 – 6 – FInite Memory Random Walks (818).mp4
│ │ 16 – 1 – Colonel Blotto Game (153).mp4
│ │ 16 – 2 – Blotto No Best Strategy (727).mp4
│ │ 16 – 3 – Applications of Colonel Blotto (708).mp4
│ │ 16 – 4 – Blotto Troop Advantages (627).mp4
│ │ 16 – 5 – Blotto and Competition (1041).mp4
│ │ 17 – 1 – Intro The Prisoners Dilemma and Collective Action (344).mp4
│ │ 17 – 2 – The Prisoners Dilemma Game (1345).mp4
│ │ 17 – 3 – Seven Ways To Cooperation (1520).mp4
│ │ 17 – 4 – Collective Action and Common Pool Resource Problems (723).mp4
│ │ 17 – 5 – No Panacea (603).mp4
│ │ 18 – 1 – Mechanism Design (400).mp4
│ │ 18 – 2 – Hidden Action and Hidden Information (953).mp4
│ │ 18 – 3 – Auctions (1959).mp4
│ │ 18 – 4 – Public Projects (1221).mp4
│ │ 19 – 1 – Replicator Dynamics (437).mp4
│ │ 19 – 2 – The Replicator Equation (1329).mp4
│ │ 19 – 3 – Fishers Theorem (1157).mp4
│ │ 19 – 4 – Variation or Six Sigma (539).mp4
│ │ 2 – 1 – Sorting and Peer Effects Introduction (511).mp4
│ │ 2 – 2 – Schellings Segregation Model (1130) (1).mp4
│ │ 2 – 3 – Measuring Segregation (1130).mp4
│ │ 2 – 4 – Peer Effects (658).mp4
│ │ 2 – 5 – The Standing Ovation Model (1805).mp4
│ │ 2 – 6 – The Identification Problem (1018).mp4
│ │ 20 – 1 – Prediction (225).mp4
│ │ 20 – 2 – Linear Models (502).mp4
│ │ 20 – 3 – Diversity Prediction Theorem (1154).mp4
│ │ 20 – 4 – The Many Model Thinker (711).mp4
│ │ 3 – 1 – Aggregation (1015).mp4
│ │ 3 – 2 – Central Limit Theorem (1852).mp4
│ │ 3 – 3 – Six Sigma (511).mp4
│ │ 3 – 4 – Game of Life (1436).mp4
│ │ 3 – 5 – Cellular Automata (1807).mp4
│ │ 3 – 6 – Preference Aggregation (1219).mp4
│ │ 4 – 1 – Introduction to Decision Making (537).mp4
│ │ 4 – 2 – Multi-Criterion Decision Making (818).mp4
│ │ 4 – 3 – Spatial Choice Models (1108).mp4
│ │ 4 – 4 – Probability The Basics (1006).mp4
│ │ 4 – 5 – Decision Trees (1438).mp4
│ │ 4 – 6 – Value of Information (841).mp4
│ │ 5 – 1 – Thinking Electrons Modeling People (629).mp4
│ │ 5 – 2 – Rational Actor Models (1609).mp4
│ │ 5 – 3 – Behavioral Models (1249).mp4
│ │ 5 – 4 – Rule Based Models (1230).mp4
│ │ 5 – 5 – When Does Behavior Matter (1240).mp4
│ │ 6 – 1 – Introduction to Linear Models (427).mp4
│ │ 6 – 2 – Categorical Models (1513).mp4
│ │ 6 – 3 – Linear Models (810).mp4
│ │ 6 – 4 – Fitting Lines to Data (1148).mp4
│ │ 6 – 5 – Reading Regression Output (1144).mp4
│ │ 6 – 6 – From Linear to Nonlinear (611).mp4
│ │ 6 – 7 – The Big Coefficient vs The New Reality (1126).mp4
│ │ 7 – 1 – Tipping Points (558).mp4
│ │ 7 – 2 – Percolation Models (1148).mp4
│ │ 7 – 3 – Contagion Models 1 Diffusion (724).mp4
│ │ 7 – 4 – Contagion Models 2 SIS Model (912).mp4
│ │ 7 – 5 – Classifying Tipping Points (826).mp4
│ │ 7 – 6 – Measuring Tips (1339).mp4
│ │ 8 – 1 – Introduction To Growth (643).mp4
│ │ 8 – 2 – Exponential Growth (1053).mp4
│ │ 8 – 3 – Basic Growth Model (1359).mp4
│ │ 8 – 4 – Solow Growth Model (1141).mp4
│ │ 8 – 5 – WIll China Continue to Grow (1155).mp4
│ │ 8 – 6 – Why Do Some Countries Not Grow (1130).mp4
│ │ 9 – 1 – Problem Solving and Innovation (506).mp4
│ │ 9 – 2 – Perspectives and Innovation (1722).mp4
│ │ 9 – 3 – Heuristics (929).mp4
│ │ 9 – 4 – Teams and Problem Solving (1105).mp4
│ │ 9 – 5 – Recombination (1102).mp4
│ │
│ └─modelthinkingzh-001
│ │ Model Thinking Resources.pdf
│ │ Model Thinking Resources_2.pdf
│ │ modelthinking.01.01.PPT.pdf
│ │ modelthinking.01.02.PPT.pdf
│ │ modelthinking.08.07.PPT.pdf
│ │
│ ├─week01
│ │ 1 – 1 – 1.1 欢迎和致谢 Welcome & Thanks (3-58).mp4
│ │ 1 – 2 – 1.2 一对多和多对一 One to Many & Many to One (8-59).mp4
│ │ 1 – 3 – 1.3 为什么要运用模型 Why Model- (8-53).mp4
│ │ 1 – 4 – 1.4 睿智的世界公民 Intelligent Citizens of the World (11-31).mp4
│ │ 1 – 5 – 1.5 思考更清晰 Thinking More Clearly (10-50).mp4
│ │ 1 – 6 – 1.6 使用和理解数据 Using & Understanding Data (10-14).mp4
│ │ 1 – 7 – 1.7 使用模型做决定、策略和设计 Using Models to Decide, Strategize & Design (15-26).mp4
│ │
│ ├─week02
│ │ 2 – 1 – 2.1 分类和同群效应简介 Sorting & Peer Effects Introduction (5-11).mp4
│ │ 2 – 2 – 2.2 谢林的隔离模型 Schelling-'s Segregation Model (11-30).mp4
│ │ 2 – 3 – 2.3 测量隔离 Measuring Segregation (11-30).mp4
│ │ 2 – 4 – 2.4 同群效应 Peer Effects (6-58).mp4
│ │ 2 – 5 – 2.5 起立鼓掌模型 The Standing Ovation Model (18-05).mp4
│ │ 2 – 6 – 2.6 识别问题 The Identification Problem (10-18).mp4
│ │
│ ├─week03
│ │ 3 – 1 – 3.1) 聚合 Aggregation (10-15).mp4
│ │ 3 – 2 – 3.2) 中心极限定理 Central Limit Theorem (18-52).mp4
│ │ 3 – 3 – 3.3) 六西格玛 Six Sigma (5-11).mp4
│ │ 3 – 4 – 3.4) 生命游戏 Game of Life (14-36).mp4
│ │ 3 – 5 – 3.5) 细胞自动机 Cellular Automata (18-07).mp4
│ │ 3 – 6 – 3.6) 偏好聚合 Preference Aggregation (12-19).mp4
│ │
│ ├─week04
│ │ 4 – 1 – 4.1) 决策模型介绍 Introduction to Decision Making (5-37).mp4
│ │ 4 – 2 – 4.2) 多准则决策 Multi-Criterion Decision Making (8-18).mp4
│ │ 4 – 3 – 4.3) 空间投票模型 Spatial Choice Models (11-08).mp4
│ │ 4 – 4 – 4.4) 概率基础 Probability- The Basics (10-06).mp4
│ │ 4 – 5 – 4.5) 决策树 Decision Trees (14-38).mp4
│ │ 4 – 6 – 4.6) 信息的价值 Value of Information (8-41).mp4
│ │
│ ├─week05
│ │ 5 – 1 – 5.1) 人类模型：电子思维 Thinking Electrons- Modeling People (6-29).mp4
│ │ 5 – 2 – 5.2) 理性行为者模型 Rational Actor Models (16-09).mp4
│ │ 5 – 3 – 5.3) 行为模型 Behavioral Models (12-49).mp4
│ │ 5 – 4 – 5.4) 基于规则的模型 Rule Based Models (12-30).mp4
│ │ 5 – 5 – 5.5) 行为什么时候重要？When Does Behavior Matter- (12-40).mp4
│ │
│ ├─week06
│ │ 6 – 1 – 6.1) 线性模型介绍 Introduction to Linear Models (4-27).mp4
│ │ 6 – 2 – 6.2) 分类模型 Categorical Models (15-13).mp4
│ │ 6 – 3 – 6.3) 线性模型 Linear Models (8-10).mp4
│ │ 6 – 4 – 6.4) 拟合数据 Fitting Lines to Data (11-48).mp4
│ │ 6 – 5 – 6.5) 读取回归输出 Reading Regression Output (11-44).mp4
│ │ 6 – 6 – 6.6) 从线性到非线性 From Linear to Nonlinear (6-11).mp4
│ │ 6 – 7 – 6.7) 大系数和新现实思维 The Big Coefficient vs The New Reality (11-26).mp4
│ │
│ ├─week07
│ │ 7 – 1 – 7.1) 临界点 Tipping Points (5-58).mp4
│ │ 7 – 2 – 7.2) 渗透模型 Percolation Models (11-48).mp4
│ │ 7 – 3 – 7.3) 传染病模型 1- 扩散 Contagion Models 1- Diffusion (7-24).mp4
│ │ 7 – 4 – 7.4) 传染病模型 2- SIS模型 Contagion Models 2- SIS Model (9-12).mp4
│ │ 7 – 5 – 7.5) 划分临界点 Classifying Tipping Points (8-26).mp4
│ │ 7 – 6 – 7.6) 测量建议 Measuring Tips (13-39).mp4
│ │
│ ├─week08
│ │ 8 – 1 – 8.1) 增长介绍 Introduction To Growth (6-43).mp4
│ │ 8 – 2 – 8.2) 指数增长 Exponential Growth (10-53).mp4
│ │ 8 – 3 – 8.3) 基础增长模型 Basic Growth Model (13-59).mp4
│ │ 8 – 4 – 8.4) 索洛增长模型 Solow Growth Model (11-41).mp4
│ │ 8 – 5 – 8.5) 中国会持续增长吗？WIll China Continue to Grow- (11-55).mp4
│ │ 8 – 6 – 8.6) 为何一些国家没有增长？Why Do Some Countries Not Grow- (11-30).mp4
│ │ 8 – 7 – 8.7) 皮凯蒂的资本论- 一个简单模型的力量 Piketty-'s Capital- The Power of a Simple Model (8-41).mp4
│ │
│ ├─week09
│ │ 9 – 1 – 9.1) 问题解决和创新 Problem Solving and Innovation (5-06).mp4
│ │ 9 – 2 – 9.2) 视角与创新 Perspectives and Innovation (16-57).mp4
│ │ 9 – 3 – 9.3) 启发式探索 Heuristics (9-29).mp4
│ │ 9 – 4 – 9.4) 团队与问题解决 Teams and Problem Solving (11-05).mp4
│ │ 9 – 5 – 9.5) 重组 Recombination (11-02).mp4
│ │
│ ├─week10
│ │ 10 – 1 – 10.1) 马尔科夫模型 Markov Models (4-26).mp4
│ │ 10 – 2 – 10.2) 一个简单的马尔科夫模型 A Simple Markov Model (11-27).mp4
│ │ 10 – 3 – 10.3) 马尔科夫民主化模型 Markov Model of Democratization (8-21).mp4
│ │ 10 – 4 – 10.4) 马尔科夫收敛定理 Markov Convergence Theorem (10-33).mp4
│ │ 10 – 5 – 10.5) 马尔科夫模型延伸 Exapting the Markov Model (10-11).mp4
│ │
│ ├─week11
│ │ 11 – 1 – 11.1) 李雅普诺夫函数 Lyapunov Functions (9-13).mp4
│ │ 11 – 2 – 11.2) 城市的组织 The Organization of Cities (12-14).mp4
│ │ 11 – 3 – 11.3) 交换经济与外部效应 Exchange Economies and Externalities (9-18).mp4
│ │ 11 – 4 – 11.4) 达到收敛与最优的时间 Time to Convergence and Optimality (8-04).mp4
│ │ 11 – 5 – 11.5) 李雅普诺夫函数深入 Lyapunov- Fun and Deep (8-40).mp4
│ │ 11 – 6 – 11.6) 李雅普诺夫或马尔科夫函数 Lyapunov or Markov (7-24).mp4
│ │
│ ├─week12
│ │ 12 – 1 – 12.1) 协调与文化 Coordination and Culture (3-37).mp4
│ │ 12 – 2 – 12.2) 什么是文化，我们为什么要关注 What Is Culture And Why Do We Care
│ │ 12 – 2 – 12.2) 什么是文化，我们为什么要关注 What Is Culture And Why Do We Care- (15-43).mp4
│ │ 12 – 3 – 12.3) 纯协调博弈 Pure Coordination Game (13-48).mp4
│ │ 12 – 4 – 12.4) 文化的兴起 Emergence of Culture (11-01).mp4
│ │ 12 – 5 – 12.5) 协调与一致 Coordination and Consistency (17-03).mp4
│ │
│ ├─week13
│ │ 13 – 1 – 13.1) 路径依赖 Path Dependence (7-23).mp4
│ │ 13 – 2 – 13.2) 瓮模型 Urn Models (16-26).mp4
│ │ 13 – 3 – 13.3) 瓮模型中的数学 Mathematics on Urn Models (14-46).mp4
│ │ 13 – 4 – 13.4) 路径依赖与混乱 Path Dependence and Chaos (11-08).mp4
│ │ 13 – 5 – 13.5) 路径依赖与收益递增 Path Dependence and Increasing Returns (12-31).mp4
│ │ 13 – 6 – 13.6) 路径依赖或临界点 Path Dependent or Tipping Point (9-52).mp4
│ │
│ ├─week14
│ │ 14 – 1 – 14.1) 网络 Networks (7-04).mp4
│ │ 14 – 2 – 14.2) 网络的结构 The Structure of Networks (19-30).mp4
│ │ 14 – 3 – 14.3) 网络形成的逻辑 The Logic of Network Formation (10-03).mp4
│ │ 14 – 4 – 14.4) 网络函数 Network Function (13-10).mp4
│ │
│ ├─week15
│ │ 15 – 1 – 15.1) 随机性和随机游走模型 Randomness and Random Walk Models (3-05).mp4
│ │ 15 – 2 – 15.2) 随机性的来源 Sources of Randomness (5-15).mp4
│ │ 15 – 3 – 15.3) 技能和运气 Skill and Luck (8-28).mp4
│ │ 15 – 4 – 15.4) 随机游走 Random Walks (12-29).mp4
│ │ 15 – 5 – 15.5) 随机游走和华尔街 Random Walks and Wall Street (7-51).mp4
│ │ 15 – 6 – 15.6) 有限记忆随机游走 Finite Memory Random Walks (8-18).mp4
│ │
│ ├─week16
│ │ 16 – 1 – 16.1) 上校赛局博弈 Colonel Blotto Game (1-53).mp4
│ │ 16 – 2 – 16.2) 上校赛局：无最佳策略 Blotto- No Best Strategy (7-27).mp4
│ │ 16 – 3 – 16.3) Blotto上校赛局的应用 Applications of Colonel Blotto (7-08).mp4
│ │ 16 – 4 – 16.4) Blotto上校赛局：军队优势 Blotto- Troop Advantages (6-27).mp4
│ │ 16 – 5 – 16.5) 上校赛局和竞争 Blotto and Competition (10-41).mp4
│ │
│ ├─week17
│ │ 17 – 1 – 17.1) 简介：囚徒困境和集体行动 Intro- The Prisoners-' Dilemma and Collective Action (3-44).mp4
│ │ 17 – 2 – 17.2) 囚徒困境博弈 The Prisoners-' Dilemma Game (13-45).mp4
│ │ 17 – 3 – 17.3) 合作的七种方式 Seven Ways To Cooperation (15-20).mp4
│ │ 17 – 4 – 17.4) 集体行动和公共资源问题 Collective Action and Common Pool Resource Problems (7-23).mp4
│ │ 17 – 5 – 17.5) 没有万灵药 No Panacea (6-03).mp4
│ │
│ └─week18
│ 18 – 1 – 18.1) 机制设计 Mechanism Design (4-00).mp4
│ 18 – 2 – 18.2) 隐藏行动和隐藏信息 Hidden Action and Hidden Information (9-53).mp4
│ 18 – 3 – 18.3) 拍卖 Auctions (19-59).mp4
│ 18 – 4 – 18.4) 公众项目 Public Projects (12-21).mp4
│
├─data analysis and statistical inference
│ 8 – 1 – Review – Frequentist vs. Bayesian Inference (28-27).mp4
│ Unit 6.zip
│ unit 7.zip
│ Week 1.zip
│ week 2.zip
│ week 3.zip
│ week 4.zip
│ week 5.zip
│
├─Data Visualization
│ ├─01_Week_1
│ │ 01_1.1.1._Introduction_00-11-58.mp4
│ │ 02_1.1.2._Some_Books_on_Data_Visualization_00-03-21.mp4
│ │ 03_1.1.3._Overview_of_Visualization_00-11-02.mp4
│ │ 04_1.2.1._2-D_Graphics_00-10-09.mp4
│ │ 05_SVG-example_00-01-34.mp4
│ │ 06_1.2.2._2-D_Drawing_00-09-11.mp4
│ │ 07_1.2.3._3-D_Graphics_00-08-39.mp4
│ │ 08_1.2.4._Photorealism_00-10-05.mp4
│ │ 09_1.2.5._Non-Photorealism_00-06-09.mp4
│ │ 10_1.3.1._The_Human_00-11-08.mp4
│ │ 11_1.3.2._Memory_00-12-16.mp4
│ │ 12_1.3.3._Reasoning_00-07-24.mp4
│ │ 13_1.3.4._The_Human_Retina_00-10-22.mp4
│ │ 14_1.3.5._Perceiving_Two_Dimensions_00-08-23.mp4
│ │ 15_1.3.6._Perceiving_Perspective_00-08-36.mp4
│ │
│ ├─02_Week_2
│ │ 01_2.1.0._Module_2_Introduction_00-02-49.mp4
│ │ 02_2.1.1._Data_00-07-44.mp4
│ │ 03_2.1.2._Mapping_00-09-04.mp4
│ │ 04_2.1.3._Charts_00-09-24.mp4
│ │ 05_2.2.1._Glyphs_Part_1_00-04-32.mp4
│ │ 06_2.2.1._Glyphs_Part_2_00-06-30.mp4
│ │ 07_2.2.2._Parallel_Coordinates_00-08-34.mp4
│ │ 08_2.2.3._Stacked_Graphs_Part_1_00-05-56.mp4
│ │ 09_2.2.3._Stacked_Graphs_Part_2_00-06-30.mp4
│ │ 10_2.3.1._Tuftes_Design_Rules_00-12-14.mp4
│ │ 11_2.3.2._Using_Color_00-11-28.mp4
│ │
│ ├─03_Week_3
│ │ 01_3.1.0_Module_3_Introduction_00-01-15.mp4
│ │ 02_3.1.1._Graphs_and_Networks_00-08-16.mp4
│ │ 03_3.1.2._Embedding_Planar_Graphs_00-11-37.mp4
│ │ 04_3.1.3._Graph_Visualization_00-13-50.mp4
│ │ 05_3.1.4._Tree_Maps_00-09-21.mp4
│ │ 06_3.2.1._Principal_Component_Analysis_00-08-04.mp4
│ │ 07_3.2.2._Multidimensional_Scaling_00-06-48.mp4
│ │ 08_3.3.1._Packing_00-12-52.mp4
│ │
│ └─04_Week_4
│ 01_4.1.0._Module_4_Introduction_00-00-55.mp4
│ 02_4.1.1._Visualization_Systems_00-03-20.mp4
│ 03_4.1.2._The_Information_Visualization_Mantra-_Part_1_00-09-05.mp4
│ 04_4.1.2._The_Information_Visualization_Mantra-_Part_2_00-09-07.mp4
│ 05_4.1.2._The_Information_Visualization_Mantra-_Part_3_00-05-49.mp4
│ 06_4.1.3._Database_Visualization_Part-_1_00-12-26.mp4
│ 07_4.1.3._Database_Visualization_Part-_2_00-08-10.mp4
│ 08_4.1.3._Database_Visualization_Part-_3_00-09-46.mp4
│ 09_4.2.1._Visualization_System_Design_00-14-26.mp4
│
├─Dino 101 Dinosaur Paleobiology
│ │ coursedescriptions.pdf
│ │ dino101-course-outline.pdf
│ │ dino101-course-teaching-outcomes.pdf
│ │ Glossary V2.pdf
│ │
│ ├─Lesson 1 Appearance and Anatomy
│ │ 1 – 1 – Introduction (7_31).mp4
│ │ 1 – 2 – Size (4_33).mp4
│ │ 1 – 3 – Skeleton (12_46).mp4
│ │ 1 – 4 – Saurischians (7_28).mp4
│ │ 1 – 5 – Ornithischians (10_03).mp4
│ │ 1 – 6 – Appearance (13_11).mp4
│ │ 1 – 7 – Muscles (4_58).mp4
│ │ Lesson 1 the Skeleton V2.pdf
│ │
│ ├─Lesson 10 Paleogeography and Plate Tectonics
│ │ 10 – 1 – Paleogeography (7_45).mp4
│ │ 10 – 2 – Continental Movement (6_32).mp4
│ │ 10 – 3 – Effect on Dinosaurs (11_58).mp4
│ │ Lesson 10 Palaeogeography and Plate Tectonics V2.pdf
│ │
│ ├─Lesson 11 Dinosaur Origins
│ │ 11 – 1 – Origins (3_07).mp4
│ │ 11 – 2 – Diapsids (9_50).mp4
│ │ 11 – 3 – Rise of the Dinosaurs (6_18).mp4
│ │ Lesson 11 Dinosaur Origins V2.pdf
│ │
│ ├─Lesson 12 Dinosaur Extinction
│ │ 12 – 1 – Extinction (9_21).mp4
│ │ 12 – 2 – Habitat Loss (5_13).mp4
│ │ 12 – 3 – Chixulub Impactor (12_14).mp4
│ │ 12 – 4 – Resurrecting Dinosaurs (4_36).mp4
│ │ Lesson 12 Dinosaur Extinction V2.pdf
│ │ Lesson 12 Dinosaur Extinction.pdf
│ │
│ ├─Lesson 2 Death and Fossilization
│ │ 2 – 1 – Taphonomy (9_10).mp4
│ │ 2 – 2 – Fossilization (8_05).mp4
│ │ 2 – 3 – Field Work (20_23).mp4
│ │ Lesson 2 Death and Fossilization V2.pdf
│ │
│ ├─Lesson 3 Eating
│ │ 3 – 1 – Types of Eaters (7_14).mp4
│ │ 3 – 2 – Teeth (7_27).mp4
│ │ 3 – 3 – Claws (3_09).mp4
│ │ 3 – 4 – Determining Diet (11_10).mp4
│ │ Lesson 3 Eating V2.pdf
│ │
│ ├─Lesson 4 Moving Around
│ │ 4 – 1 – Stance (5_23).mp4
│ │ 4 – 2 – Limbs (12_39).mp4
│ │ 4 – 3 – Trackways (4_41).mp4
│ │ 4 – 4 – Metabolism (5_23).mp4
│ │ Lesson 4 Moving Around V2.pdf
│ │
│ ├─Lesson 5 Birth, Growth, and Reproduction
│ │ 5 – 1 – Eggs (4_27).mp4
│ │ 5 – 2 – Young Dinosaurs (14_30).mp4
│ │ 5 – 3 – Males & Females (9_27).mp4
│ │ Lesson 5 Birth Growth and Reproduction V2.pdf
│ │
│ ├─Lesson 6 Attack and Defense
│ │ 6 – 1 – Defensive Adaptations (13_49).mp4
│ │ 6 – 2 – Offensive Adaptations (15_24).mp4
│ │ 6 – 3 – Intraspecies Interactions (7_34).mp4
│ │ Lesson 6 Attack and Defense V2.pdf
│ │
│ ├─Lesson 7 What is a Species
│ │ 7 – 1 – Naming Species (9_20).mp4
│ │ 7 – 2 – Holotype (6_13).mp4
│ │ 7 – 3 – Differentiating Species (11_17).mp4
│ │ Lesson 7 What is a Species V2.pdf
│ │
│ ├─Lesson 8 Evolution
│ │ 8 – 1 – Clades (10_49).mp4
│ │ 8 – 2 – Convergence (9_46).mp4
│ │ 8 – 3 – Birds (9_20).mp4
│ │ Lesson 8 Evolution V2.pdf
│ │
│ └─Lesson 9 Stratigraphy and Geologic Time
│ 9 – 1 – Deep Time (13_19).mp4
│ 9 – 2 – Stratigraphy (7_53).mp4
│ 9 – 3 – The Age of Dinosaurs (5_47).mp4
│ Lesson 9 Stratigraphy and Geologic Time V2.pdf
│
├─Getting and Cleaning Data
│ ├─Week1
│ │ 1 – 1 – Obtaining Data Motivation (5-38) .mp4
│ │ 1 – 2 – Raw and Processed Data (7-07).mp4
│ │ 1 – 3 – Components of Tidy Data (9-25).mp4
│ │ 1 – 4 – Downloading Files (7-09).mp4
│ │ 1 – 5 – Reading Local Files (4-55).mp4
│ │ 1 – 6 – Reading Excel Files (3-55).mp4
│ │ 1 – 7 – Reading XML (12-39).mp4
│ │ 1 – 8 – Reading JSON (5-03).mp4
│ │ 1 – 9 – The data.table Package (11-18).mp4
│ │ 01_01_obtainingDataMotivation.pdf
│ │ 01_02_rawAndProcessedData.pdf
│ │ 01_03_componentsOfTidyData.pdf
│ │ 01_04_downLoadingFiles.pdf
│ │ 01_05_readingLocalFiles.pdf
│ │ 01_06_readingExcelFiles.pdf
│ │ 01_07_readingXML.pdf
│ │ 01_08_readingJSON.pdf
│ │ 01_09_dataTable.pdf
│ │
│ ├─Week2
│ │ 2 – 1 – Reading from MySQL (14-44).mp4
│ │ 2 – 2 – Reading from HDF5 (6-45).mp4
│ │ 2 – 3 – Reading from The Web (6-47).mp4
│ │ 2 – 4 – Reading From APIs (7-57).mp4
│ │ 2 – 5 – Reading From Other Sources (4-44).mp4
│ │ 02_01_readingMySQL.pdf
│ │ 02_02_readingHDF5.pdf
│ │ 02_03_readingFromTheWeb.pdf
│ │ 02_04_readingFromAPIs.pdf
│ │ 02_05_readingFromOtherSources.pdf
│ │
│ ├─Week3
│ │ 3 – 1 – Subsetting and Sorting (6-51).mp4
│ │ 3 – 2 – Summarizing Data (11-37).mp4
│ │ 3 – 3 – Creating New Variables (10-32).mp4
│ │ 3 – 4 – Reshaping Data (9-13).mp4
│ │ 3 – 5 – Merging Data (6-19).mp4
│ │ 03_01_subsettingAndSorting.pdf
│ │ 03_02_summarizingData.pdf
│ │ 03_03_creatingNewVariables.pdf
│ │ 03_04_reshapingData.pdf
│ │ 03_05_mergingData.pdf
│ │
│ └─Week4
│ 4 – 1 – Editing Text Variables (10-46).mp4
│ 4 – 2 – Regular Expressions I (5-16).mp4
│ 4 – 3 – Regular Expressions II (8-00).mp4
│ 4 – 4 – Working with Dates (6-02).mp4
│ 4 – 5 – Data Resources (3-33).mp4
│ 04_01_editingTextVariables.pdf
│ 04_02_regularExpressions.pdf
│ 04_03_regularExpressionsII.pdf
│ 04_04_workingWithDates.pdf
│ 04_05_dataResources.pdf
│
├─Mining Massive Datasets
│ │ bookL.pdf
│ │
│ ├─01_Week_1_Materials
│ │ 01_Distributed_File_Systems_15-50.mp4
│ │ 02_The_MapReduce_Computational_Model_22-04.mp4
│ │ 03_Scheduling_and_Data_Flow_12-43.mp4
│ │ 04_Combiners_and_Partition_Functions_12-17_Advanced.mp4
│ │ 05_Link_Analysis_and_PageRank_9-39.mp4
│ │ 06_PageRank-_The_Flow_Formulation_9-16.mp4
│ │ 07_PageRank-_The_Matrix_Formulation_8-02.mp4
│ │ 08_PageRank-_Power_Iteration_10-34.mp4
│ │ 09_PageRank-_The_Google_Formulation_12-08.mp4
│ │ 10_Why_Teleports_Solve_the_Problem_12-26.mp4
│ │ 11_How_we_Really_Compute_PageRank_13-49.mp4
│ │ 01_Distributed_File_Systems_15-50.pdf
│ │ 02_The_MapReduce_Computational_Model_22-04.pdf
│ │ 03_Scheduling_and_Data_Flow_12-43.pdf
│ │ 04_Combiners_and_Partition_Functions_12-17_Advanced.pdf
│ │ 05_Link_Analysis_and_PageRank_9-39.pdf
│ │ 06_PageRank-_The_Flow_Formulation_9-16.pdf
│ │ 07_PageRank-_The_Matrix_Formulation_8-02.pdf
│ │ 08_PageRank-_Power_Iteration_10-34.pdf
│ │ 09_PageRank-_The_Google_Formulation_12-08.pdf
│ │ 10_Why_Teleports_Solve_the_Problem_12-26.pdf
│ │ 11_How_we_Really_Compute_PageRank_13-49.pdf
│ │
│ ├─02_Week_2_Materials
│ │ 01_Finding_Similar_Sets_13-37.mp4
│ │ 02_Minhashing_25-18.mp4
│ │ 03_Locality-Sensitive_Hashing_19-24.mp4
│ │ 04_Applications_of_LSH_11-40.mp4
│ │ 05_Fingerprint_Matching_7-07.mp4
│ │ 06_Finding_Duplicate_News_Articles_6-08.mp4
│ │ 07_Distance_Measures_22-39.mp4
│ │ 08_Nearest_Neighbor_Learning_11-39.mp4
│ │ 09_Frequent_Itemsets_29-50.mp4
│ │ 10_A-Priori_Algorithm_13-07.mp4
│ │ 11_Improvements_to_A-Priori_17-26__Advanced.mp4
│ │ 12_All_or_Most_Frequent_Itemsets_in_2_Passes_14-40_Advanced.mp4
│ │ 01_Finding_Similar_Sets_13-37.pdf
│ │ 02_Minhashing_25-18.pdf
│ │ 03_Locality-Sensitive_Hashing_19-24.pdf
│ │ 04_Applications_of_LSH_11-40.pdf
│ │ 05_Fingerprint_Matching_7-07.pdf
│ │ 06_Finding_Duplicate_News_Articles_6-08.pdf
│ │ 07_Distance_Measures_22-39.pdf
│ │ 08_Nearest_Neighbor_Learning_11-39.pdf
│ │ 09_Frequent_Itemsets_29-50.pdf
│ │ 10_A-Priori_Algorithm_13-07.pdf
│ │ 11_Improvements_to_A-Priori_17-26__Advanced.pdf
│ │ 12_All_or_Most_Frequent_Itemsets_in_2_Passes_14-40_Advanced.pdf
│ │
│ ├─03_Week_3_Materials
│ │ 01_Community_Detection_in_Graphs-_Motivation_5-44.mp4
│ │ 02_The_Affiliation_Graph_Model_10-04.mp4
│ │ 03_From_AGM_to_BIGCLAM_8-48.mp4
│ │ 04_Solving_the_BIGCLAM_9-19.mp4
│ │ 05_Detecting_Communities_as_Clusters_8-39_Advanced.mp4
│ │ 06_What_Makes_a_Good_Cluster_8-48_Advanced.mp4
│ │ 07_The_Graph_Laplacian_Matrix_6-51_Advanced.mp4
│ │ 08_Examples_of_Eigendecompositions_of_Graphs_6-16_Advanced.mp4
│ │ 09_Defining_the_Graph_Laplacian_3-27_Advanced.mp4
│ │ 10_Spectral_Graph_Partitioning-_Finding_a_Partition_13-25_Advanced.mp4
│ │ 11_Spectral_Clustering-_Three_Steps_7-17_Advanced.mp4
│ │ 12_Analysis_of_Large_Graphs-_Trawling_9-02_Advanced.mp4
│ │ 13_Mining_Data_Streams_12-01.mp4
│ │ 14_Counting_1s_29-00_Advanced.mp4
│ │ 15_Bloom_Filters_18-00.mp4
│ │ 16_Sampling_a_Stream_11-30.mp4
│ │ 17_Counting_Distinct_Elements_25-59_Advanced.mp4
│ │ 01_Community_Detection_in_Graphs-_Motivation_5-44.pdf
│ │ 02_The_Affiliation_Graph_Model_10-04.pdf
│ │ 03_From_AGM_to_BIGCLAM_8-48.pdf
│ │ 04_Solving_the_BIGCLAM_9-19.pdf
│ │ 05_Detecting_Communities_as_Clusters_8-39_Advanced.pdf
│ │ 06_What_Makes_a_Good_Cluster_8-48_Advanced.pdf
│ │ 07_The_Graph_Laplacian_Matrix_6-51_Advanced.pdf
│ │ 08_Examples_of_Eigendecompositions_of_Graphs_6-16_Advanced.pdf
│ │ 09_Defining_the_Graph_Laplacian_3-27_Advanced.pdf
│ │ 10_Spectral_Graph_Partitioning-_Finding_a_Partition_13-25_Advanced.pdf
│ │ 11_Spectral_Clustering-_Three_Steps_7-17_Advanced.pdf
│ │ 12_Analysis_of_Large_Graphs-_Trawling_9-02_Advanced.pdf
│ │ 13_Mining_Data_Streams_12-01.pdf
│ │ 14_Counting_1s_29-00_Advanced.pdf
│ │ 15_Bloom_Filters_18-00.pdf
│ │ 16_Sampling_a_Stream_11-30.pdf
│ │ 17_Counting_Distinct_Elements_25-59_Advanced.pdf
│ │
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