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温州大学《机器学习》公开课合集，黄海广老师主讲，适合本科三年级以上学生学习。本课程用通俗和结合案例的方式，讲解机器学习算法，如经典算法：线性回归、逻辑回归、决策树等，也将讲解近几年才出现的如XGBoost、LightGBM等集成学习算法。通过本课程，你不仅得到理论基础的学习，而且获得那些利用机器学习解决问题的实用技术，包括机器学习工具的使用等等。
课程大纲、课程练习题请到中国大学慕课：https://www.icourse163.org/course/WZU-1464096179
课程代码分享在github：https://github.com/fengdu78/WZU-machine-learning-course
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MIT《量化金融的数学方法》（中英字幕）| MIT Mathematical Methods for Quantitative Finance
2.3万播放
MIT《量化金融的数学方法》1.概率
01:57:22
2.离散时间随机过程简介
02:19:36
3.时间序列模型
02:32:30
4.连续时间随机过程简介
02:18:36
5.连续时间财务
01:53:54
6.资产定价的线性代数
01:35:37
7.优化
01:54:59
8.最佳决策和最佳策略
02:45:34
【精译】金融数学
6524播放
01 2021 开场白
15:20
02 讲座1(A)：集合和n元组
13:32
03 讲座1(B)：集合和n元组
21:40
04 讲座2（A）：量词和函数1
16:50
05 讲座2（B）：量词和函数1
36:26
06 讲座3（A）：量词和函数2
35:02
07 讲座3（B）：量词和函数2
22:15
08 讲座 4(A)：统一 n 元组、序列、函数和子集
20:18
09 讲座 4(B)：统一 n 元组、序列、函数和子集
18:50
10 5(A)：逻辑1（陈述和真值）
24:27
11 5(B)：逻辑1（真值表和复合语句）
18:13
12 5(C)：逻辑1（蕴涵；德摩根定律）
23:13
13 6(A)：逻辑2（含义问题）
24:45
14 6(B)：逻辑2（证明策略）
14:34
15 6(C)：逻辑2（证明策略）
31:19
16 7(A)：归纳证明：它是什么，它是如何工作的？
22:36
17 讲座 7(B)： 归纳证明
27:07
18 第8课：向量空间的基础：Rn的几何和代数（修订版）
30:21
19 9(A)：欧几里得空间
31:04
20 9(B)：欧几里得空间：柯西-施瓦茨不等式和三角不等式，点积，超平面
27:26
21 10(A)：欧几里得空间：邻域、开集和闭集
28:32
22 22（B）：欧几里得空间：例子和定理
30:30
23 讲座11：向量空间
41:40
24 讲座12(A)：向量子空间
28:40
25 25（B）：向量子空间
32:49
26 讲座13(A)：线性组合
35:23
27 讲座13(B)：线性组合
28:06
28 讲座14(A)：线性独立和基础
31:45
29 讲座14(B)：线性独立和基础
39:47
30 15(A)：线性函数
20:49
31 15(B)：线性函数
24:05
32 15(C)：线性函数
21:07
33 16(A)：凸性
25:20
34 16(B)：凸性
26:32
35 16(C)：凸性
07:23
36 17(A)：凹凸函数
21:14
37 18(A)：替代规范和度量
32:35
38 18(B)：替代规范和度量
20:39
39 18(C)：替代规范和度量
14:35
40 18(D)：替代规范和度量
16:32
41 19(A)：序列
25:24
42 19(B)：序列
15:51
43 19(C)：序列
31:32
44 20(A)：有界序列和子序列
19:26
45 20(B)：有界序列：单调收敛定理
29:01
46 20(C)：有界序列：波尔查诺-魏尔斯特拉斯定理
32:05
47 21(A)：连续函数
23:11
48 21(B)：连续函数
19:38
49 22(A)：连续函数2
31:37
50 22(B)：连续函数2（修订版）
24:35
51 23(A)：紧集和度量空间；波尔查诺-魏尔斯特拉斯定理
25:54
52 23(B)：紧集，维尔斯特拉斯定理，例子和反例
29:16
53 24(A)：近似和泰勒多项式
33:54
54 24(B)：近似和泰勒多项式，附带示例
35:43
55 25(A)：导数
28:24
56 25(B)：导数
31:28
57 26(A)： Rn中的逼近与泰勒多项式
26:55
58 26(B)：Rn中的逼近与泰勒多项式
21:39
59 27(A)：二次型：对称矩阵，几何直觉
28:26
60 27(B)：二次型：几何示例
24:57
61 第28课：二次型：定型和半定型
22:40
62 29(A)：二次型：正定性的必要和充分条件
28:09
63 29(B)：二次型：确定性的行列式条件
26:38
64 29(C)：二次型：确定性的行列式条件
22:17
65 第30课：无约束优化1
35:22
66 第31课：无约束优化2
35:27
67 讲座32：无约束优化3
15:39
68 讲座 33(A)： 全局优化
20:46
69 33(B)：可微凹函数的特征
14:10
70 33(C)：凹函数和全局优化
36:34
71 第34课：约束优化的几何学：关注梯度
33:23
72 第35课：约束优化的几何学：多重和非线性约束
42:05
73 讲座 36(A)： 解决方案函数和价值函数
40:51
74 36(B)：解函数和值函数
26:02
75 37(A)：隐函数定理：当参数变化时，解如何变化
17:48
76 37(B)：隐函数定理
26:25
77 37(C)：隐函数定理
23:40
78 37(D)：隐函数定理
30:19
79 38(A)：包络定理：最优值如何变化
30:36
80 38(B)：约束优化的包络定理
23:57
81 39(A)：包络定理和影子值
20:09
82 39(B)：包络定理：霍特林引理
13:50
83 39(C)：包络定理：谢泼德引理
34:26
84 40(A)：库恩-塔克条件：概念和几何洞察力
26:16
85 40(B)：库恩-塔克条件和定理
23:37
86 40(C)：库恩-塔克条件：一个例子
19:27
87 40(D)：库恩-塔克条件：两个例子
16:53
88 40(E)：库恩-塔克条件：一个角落（边界）解决方案
21:25
89 讲座 41(A)：二元关系
20:22
90 41(B)：二元关系
22:33
91 42(A)：顺序关系、偏好和效用函数
39:29
92 讲 42(B)：顺序关系和效用函数练习解答
30:10
93 43(A)：等价关系与划分
23:15
94 43(B)：等价关系与划分
35:18
95 讲 44(A)：用效用函数表示偏好
27:32
96 讲座 44(B)：用效用函数表示偏好
37:14
97 45(B)：词典式偏好
18:34
98 讲座 45(A)：词典式偏好
19:11
99 对应
26:25
100 半连续对应
29:45
随机过程 2024 张颢老师（放大高清修复）（全集）
25.3万播放
1.第1章 随机过程概念及其分类1
01:08:38
2.第1章 随机过程概念及其分类2
01:25:03
3.第1章 随机过程概念及其分类3
02:27:19
4.第2章 非平稳过程
02:29:21
5.第2章 多元相关
02:32:38
6.第3章 Gauss过程1
02:22:06
7.第3章 Gauss过程2
02:41:25
8.第3章 Gauss过程3
02:29:26
9.第3章 Gauss过程4
02:30:45
10.第3章 Gauss过程5
02:22:56
11.第4章 Poisson过程1
02:21:28
12.第4章 Poisson过程2
02:27:55
13.第4章 Poisson过程3
02:32:00
14.第4章 Poisson过程4
02:29:51
15.第5章 Markov链1
02:34:13
16.第5章 Markov链2
02:27:30
17.第5章 Markov链3
02:21:20
18.第5章 Markov链4
02:27:04
19.期末习题课
01:58:20
2.6万播放
比啃书好太多！【最优化理论完整版教程】不愧是中科大教授！3小时让我清楚了凸优化，简直不要太爽！人工智能|AI|数学基础|最优化算法|机器学习|深度学习|nlp
31.3万播放
1. 引言（1）
42:28
2. 引言（2）
45:16
3. 仿射_凸_凸锥 + 集_组合_包（1）
45:12
4. 仿射_凸_凸锥 + 集_组合_包（2）
38:04
5. 几种重要的凸集（1）
45:13
6. 几种重要的凸集（2）
44:56
7. 凸集的交集，保凸运算（1）
45:09
8. 凸集的交集，保凸运算（2）
45:49
9. 凸函数的定义和扩展
36:59
10. 凸函数定义2，常见例函数的凸性（1）
45:13
12. 函数凸性，保持函数凸性（1）
45:02
13. 函数凸性，保持函数凸性（2）
46:36
14. 复合函数保凸的条件，函数的透视（1）
44:57
15. 复合函数保凸的条件，函数的透视（2）
43:53
16. 复合函数保凸条件，函数的共轭，α-sublevel set，拟凸函数
45:08
17. 复合函数保凸条件，函数的共轭，α-sublevel set，拟凸函数
44:29
18. 课堂小测1），向量零范数的松弛形式，可微拟凸函数的一阶条件和二阶条件
23:59
19. 课堂小测1），向量零范数的松弛形式，可微拟凸函数的一阶条件和二阶条件
44:21
20. 可微拟凸函数的一阶条件的充分性证明，凸问题（1）
45:11
21. 可微拟凸函数的一阶条件的充分性证明，凸问题（2）
45:38
22. 凸优化问题，凸优化约束的降维和升维（松弛变量），拟凸优化问题，凸问题
45:13
23. 凸优化问题，凸优化约束的降维和升维（松弛变量），拟凸优化问题，凸问题
46:02
24. 凸问题的等价变换，营养食谱问题，线性分数规划，二次规划，QCQP，回
45:11
25. 凸问题的等价变换，营养食谱问题，线性分数规划，二次规划，QCQP，回
44:30
26. 投资组合问题的形式，半正定规划问题，谱范数，多目标优化问题（1）
44:21
28. 对偶性，Lagrange函数，Lagrange函数的凹性，对偶函数与
45:11
29. 对偶性，Lagrange函数，Lagrange函数的凹性，对偶函数与
39:01
30. 强对偶_弱对偶，对偶间隙，Slater条件，弱Slater条件，P_
43:34
31. 强对偶_弱对偶，对偶间隙，Slater条件，弱Slater条件，P_
44:12
32. 线性代数知识：Byod的《Convex Optimization》附
57:41
33. 线性代数知识：Byod的《Convex Optimization》附
33:35
34. KKT条件，KKT条件充要性证明（1）
44:05
35. KKT条件，KKT条件充要性证明（2）
45:51
36. 线性约束的QP问题的KKT条件，Water-filling问题的KK
45:19
37. 线性约束的QP问题的KKT条件，Water-filling问题的KK
45:38
38. 敏感性分析（1）
45:10
39. 敏感性分析（2）
45:08
40. 带等式约束的可微凸优化问题的罚函数形式，带线性不等式约束的可微凸优化
45:14
41. 带等式约束的可微凸优化问题的罚函数形式，带线性不等式约束的可微凸优化
42:54
42.（课堂小测2），函数的强凸性，Hassien矩阵的上界下界，f(x)
22:26
43.（课堂小测2），函数的强凸性，Hassien矩阵的上界下界，f(x)
42:51
44. 强凸性等价不等式及其相反性质的等价不等式，梯度下降法，算法的收敛性
45:13
45. 强凸性等价不等式及其相反性质的等价不等式，梯度下降法，算法的收敛性
45:36
46. 最速下降法（1）
45:10
47. 最速下降法（2）
43:08
48. 无约束优化问题算法选择建议，有约束优化问题（关心只含等式约束的问题）
44:53
49. 无约束优化问题算法选择建议，有约束优化问题（关心只含等式约束的问题）
43:55
50. 增广拉格朗日法，其常用技巧（分布式计算）（1）
44:19
51. 增广拉格朗日法，其常用技巧（分布式计算）（2）
47:10
52. NLP专题讲座，NLP下的KKT条件（1）
45:35
53. NLP专题讲座，NLP下的KKT条件（2）
20:40
54. 总复习
01:03:23
【MIT公开课】86岁Gilbert Strang教授2020《线性代数》更新讲解课程202005（中英字幕）
17.7万播放
Intro_ A New Way to Start Linear Algebra_1080p
04:15
Part 1_ The Column Space of a Matrix_1080p
14:00
Part 2_ The Big Picture of Linear Algebra_1080p
11:02
Part 3_ Orthogonal Vectors_1080p
14:10
Part 4_ Eigenvalues and Eigenvectors_1080p
13:42
Part 5_ Singular Values and Singular Vectors_1080p
13:15
106.2万播放
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高能预警！快放1000倍，带你看受精卵分裂全过程
728.2万播放
正片
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纯享版
02:35
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【完整版-麻省理工-线性代数】全34讲+配套教材
255.6万播放
Lec01_方程组的几何解释
39:50
Lec02_矩阵消元
47:42
Lec03_矩阵乘法和逆
46:49
Lec04_A的LU分解
49:07
Lec05_转置、置换、向量空间
47:42
Lec06_列空间和零空间
46:02
Lec07_Ax=0：主变量、特解
43:20
Lec08_Ax=b：可解性及解的结构
47:26
Lec09_线性相关性、基、维数
50:21
Lec10_四个基本子空间
49:27
Lec11_矩阵空间、秩1矩阵和小世界图
46:02
Lec12_图和网络
47:58
Lec13_复习一
47:40
Lec14_正交向量和正交子空间
49:48
Lec15_投影
48:52
Lec16_投影矩阵和最小二乘
48:06
Lec17_正交矩阵和正交化法
49:25
Lec18_行列式及性质
49:13
Lec19_行列式公式及代数余子式.
53:18
Lec20_行列式应用：克拉默法则、逆矩阵、体积
51:02
Lec21_特征值和特征向量
51:23
Lec22_对角化和矩阵乘幂
51:51
Lec23_微分方程和exp(At)
51:04
Lec24a_马尔科夫矩阵和傅里叶级数
51:12
Lec24b_复习二
48:21
Lec25_对称矩阵和正定矩阵
43:53
Lec26_复矩阵和快速傅里叶变换
47:53
Lec27_正定矩阵
50:41
Lec28_相似矩阵和若尔当标准型
45:57
Lec29_奇异值分解
41:36
Lec30_线性变换及对应矩阵
49:28
Lec31_基变换及图像压缩
50:14
Lec32_复习三
47:06
Lec33_左右逆和伪逆
41:53
Lec34_总复习
43:27
【MIT公开课】6.006 算法导论（完结·中英字幕·机翻）
9.3万播放
1 Algorithmic Thinking Peak Finding
53:22
2 Models of Computation Document Distance
48:52
3 Insertion Sort Merge Sort
51:20
4 Heaps and Heap Sort
52:32
5 Binary Search Trees BST Sort
52:40
6 AVL Trees AVL Sort
51:59
7 Counting Sort Radix Sort Lower Bounds for Sorting
52:09
8 Hashing with Chaining
51:16
9 Table Doubling Karp-Rabin
52:47
10 Open Addressing Cryptographic Hashing
50:55
11 Integer Arithmetic Karatsuba Multiplication
47:24
12 Square Roots Newtons Method
51:17
13 Breadth-First Search (BFS)
50:48
14 Depth-First Search (DFS) Topological Sort
50:31
15 Single-Source Shortest Paths Problem
53:15
16 Dijkstra
51:26
17 Bellman-Ford
48:51
18 Speeding up Dijkstra
53:16
19 Dynamic Programming I Fibonacci Shortest Paths
51:47
20 Dynamic Programming II Text Justification Blackjack
52:12
21 DP III Parenthesization Edit Distance Knapsack
52:41
22 DP IV Guitar Fingering Tetris Super Mario Bros
49:20
23 Computational Complexity
51:12
24 Topics in Algorithms Research
46:47
R1 Asymptotic Complexity Peak Finding
53:50
R2 Python Cost Model Document Distance
52:21
R3 Document Distance Insertion and Merge Sort
54:11
R5 Recursion Trees Binary Search Trees
59:16
R6 AVL Trees
53:28
R7 Comparison Sort Counting and Radix Sort
51:09
R8 Simulation Algorithms
55:39
R9 Rolling Hashes Amortized Analysis
01:01:01
R10 Quiz 1 Review
54:49
R11 Principles of Algorithm Design
58:26
R12 Karatsuba Multiplication Newtons Method
53:08
R13 Breadth-First Search (BFS)
54:53
R14 Depth-First Search (DFS)
53:39
R15 Shortest Paths
56:31
R16 Rubiks Cube StarCraft Zero
54:36
R18 Quiz 2 Review
01:05:30
R19 Dynamic Programming Crazy Eights Shortest Path
52:48
R20 Dynamic Programming Blackjack
52:58
R21 Dynamic Programming Knapsack Problem
01:09:12
R22 Dynamic Programming Dance Dance Revolution
53:16
R23 Computational Complexity
47:14
R24 Final Exam Review
51:44
Recitation 9b DNA Sequence Matching
57:28
【MIT公开课】18.065 数据分析、信号处理和机器学习中的矩阵方法 · 2018年春（完结·中英字幕·机翻）
6.8万播放
Course Introduction of 18065 by Professor Strang
07:04
An Interview with Gilbert Strang on Teaching Matrix Methods in Data Analysis Sig
08:07
1 The Column Space of A Contains All Vectors Ax
52:15
2 Multiplying and Factoring Matrices
48:26
3 Orthonormal Columns in Q Give QQ I
49:24
4 Eigenvalues and Eigenvectors
48:56
5 Positive Definite and Semidefinite Matrices
45:28
6 Singular Value Decomposition (SVD)
53:34
7 Eckart-Young The Closest Rank k Matrix to A
47:16
8 Norms of Vectors and Matrices
49:21
9 Four Ways to Solve Least Squares Problems
49:51
10 Survey of Difficulties with Ax b
49:36
11 Minimizing _x_ Subject to Ax b
50:22
12 Computing Eigenvalues and Singular Values
49:28
13 Randomized Matrix Multiplication
52:24
14 Low Rank Changes in A and Its Inverse
50:35
15 Matrices A(t) Depending on t Derivative dAdt
50:52
16 Derivatives of Inverse and Singular Values
43:08
17 Rapidly Decreasing Singular Values
50:34
18 Counting Parameters in SVD LU QR Saddle Points
49:00
19 Saddle Points Continued Maxmin Principle
52:13
20 Definitions and Inequalities
55:01
21 Minimizing a Function Step by Step
53:45
22 Gradient Descent Downhill to a Minimum
52:44
23 Accelerating Gradient Descent (Use Momentum)
49:02
24 Linear Programming and Two-Person Games
53:34
25 Stochastic Gradient Descent
53:03
26 Structure of Neural Nets for Deep Learning
53:17
27 Backpropagation Find Partial Derivatives
52:38
30 Completing a Rank-One Matrix Circulants
49:53
31 Eigenvectors of Circulant Matrices Fourier Matrix
52:37
32 ImageNet is a Convolutional Neural Network (CNN) The Convolution Rule
47:19
33 Neural Nets and the Learning Function
56:08
34 Distance Matrices Procrustes Problem
29:17
35 Finding Clusters in Graphs
34:49
36. Alan Edelman and Julia Language
38:11
[英文字幕]哈佛概率论 Stat 110 [可能是最好的概率论自学网课]
15.3万播放
Joseph Blitzstein- "The Soul of Statistics" | Harvard Thinks Big 4
14:47
Lecture 1- Probability and Counting | Statistics 110
46:30
Lecture 2- Story Proofs, Axioms of Probability | Statistics 110
45:40
Lecture 3- Birthday Problem, Properties of Probability | Statistics 110
48:55
Lecture 4- Conditional Probability | Statistics 110
49:45
Lecture 5- Conditioning Continued, Law of Total Probability | Statistics 110
50:02
Lecture 6- Monty Hall, Simpson's Paradox | Statistics 110
49:01
Lecture 7- Gambler's Ruin and Random Variables | Statistics 110
51:46
Lecture 8- Random Variables and Their Distributions | Statistics 110
50:24
Lecture 9- Expectation, Indicator Random Variables, Linearity | Statistics 110
50:23
Lecture 10- Expectation Continued | Statistics 110
50:10
Lecture 11- The Poisson distribution | Statistics 110
42:46
Lecture 12- Discrete vs. Continuous, the Uniform | Statistics 110
49:57
Lecture 12- Discrete vs. Continuous, the Uniform | Statistics 110
49:57
Lecture 13- Normal distribution | Statistics 110
51:10
Lecture 14- Location, Scale, and LOTUS | Statistics 110
48:55
Lecture 15- Midterm Review | Statistics 110
38:12
Lecture 16- Exponential Distribution | Statistics 110
18:20
Lecture 17- Moment Generating Functions | Statistics 110
50:45
Lecture 18- MGFs Continued | Statistics 110
49:41
Lecture 19- Joint, Conditional, and Marginal Distributions | Statistics 110
50:09
Lecture 20- Multinomial and Cauchy | Statistics 110
49:00
Lecture 21- Covariance and Correlation | Statistics 110
49:26
Lecture 22- Transformations and Convolutions | Statistics 110
47:46
Lecture 23- Beta distribution | Statistics 110
49:49
Lecture 24- Gamma distribution and Poisson process | Statistics 110
48:49
Lecture 25- Order Statistics and Conditional Expectation | Statistics 110
48:15
Lecture 26- Conditional Expectation Continued | Statistics 110
49:53
Lecture 27- Conditional Expectation given an R.V. | Statistics 110
50:34
Lecture 28- Inequalities | Statistics 110
47:29
Lecture 29- Law of Large Numbers and Central Limit Theorem | Statistics 110
49:48
Lecture 30- Chi-Square, Student-t, Multivariate Normal | Statistics 110
47:28
Lecture 31- Markov Chains | Statistics 110
46:38
Lecture 32- Markov Chains Continued | Statistics 110
48:24
Lecture 33- Markov Chains Continued Further | Statistics 110
47:01
Lecture 34- A Look Ahead | Statistics 110
36:59
概率论导论 Introduction to Probability 哈佛大学 Stat110
4.5万播放
Lecture 1_ Probability and Counting _ Statistics 110
46:30
Lecture 2_ Story Proofs, Axioms of Probability _ Statistics 110
45:40
Lecture 3_ Birthday Problem, Properties of Probability _ Statistics 110
48:55
Lecture 4_ Conditional Probability _ Statistics 110
49:45
Lecture 5_ Conditioning Continued, Law of Total Probability _ Statistics 110
50:02
Lecture 6_ Monty Hall, Simpson's Paradox _ Statistics 110
49:01
Lecture 7_ Gambler's Ruin and Random Variables _ Statistics 110
51:46
Lecture 8_ Random Variables and Their Distributions _ Statistics 110
50:24
Lecture 9_ Expectation, Indicator Random Variables, Linearity _ Statistics 110
50:23
Lecture 10_ Expectation Continued _ Statistics 110
50:10
Lecture 11_ The Poisson distribution _ Statistics 110
42:46
Lecture 12_ Discrete vs. Continuous, the Uniform _ Statistics 110
49:56
Lecture 13_ Normal distribution _ Statistics 110
51:10
Lecture 14_ Location, Scale, and LOTUS _ Statistics 110
48:55
Lecture 15_ Midterm Review _ Statistics 110
38:12
Lecture 16_ Exponential Distribution _ Statistics 110
18:20
Lecture 17_ Moment Generating Functions _ Statistics 110
50:45
Lecture 18_ MGFs Continued _ Statistics 110
49:41
Lecture 19_ Joint, Conditional, and Marginal Distributions _ Statistics 110
50:09
Lecture 20_ Multinomial and Cauchy _ Statistics 110
49:00
Lecture 21_ Covariance and Correlation _ Statistics 110
49:26
Lecture 22_ Transformations and Convolutions _ Statistics 110
47:46
Lecture 23 Beta distribution_ Statistics 110
49:49
Lecture 24_ Gamma distribution and Poisson process _ Statistics 110
48:49
Lecture 25_ Order Statistics and Conditional Expectation _ Statistics 110
48:15
Lecture 26_ Conditional Expectation Continued _ Statistics 110
49:53
Lecture 27_ Conditional Expectation given an R.V. _ Statistics 110
50:34
Lecture 28 Inequalities_ Statistics 110
47:29
Lecture 29_ Law of Large Numbers and Central Limit Theorem _ Statistics 110
49:48
Lecture 30_ Chi-Square, Student-t, Multivariate Normal _ Statistics 110
47:28
Lecture 31_ Markov Chains _ Statistics 110
46:38
Lecture 32_ Markov Chains Continued _ Statistics 110
48:24
Lecture 33_ Markov Chains Continued Further _ Statistics 110
47:01
Lecture 34_ A Look Ahead _ Statistics 110
36:59
Joseph Blitzstein_ _The Soul of Statistics_ _ Harvard Thinks Big 4
14:47
Statistics 110: Probability 概率论 哈佛大学（中英）
11.7万播放
Lecture 1: Probability and Counting | Statistics 110
46:30
Lecture 2: Story Proofs, Axioms of Probability | Statistics 110
45:40
Lecture 3: Birthday Problem, Properties of Probability | Statistics 110
48:55
Lecture 4: Conditional Probability | Statistics 110
49:45
Lecture 5: Conditioning Continued, Law of Total Probability | Statistics 110
50:02
Lecture 6: Monty Hall, Simpson's Paradox | Statistics 110
49:01
Lecture 7: Gambler's Ruin and Random Variables | Statistics 110
51:46
Lecture 8: Random Variables and Their Distributions | Statistics 110
50:24
Lecture 9: Expectation, Indicator Random Variables, Linearity | Statistics 110
50:23
Lecture 10: Expectation Continued | Statistics 110
50:10
Lecture 11: The Poisson distribution | Statistics 110
42:46
Lecture 12: Discrete vs. Continuous, the Uniform | Statistics 110
49:57
Lecture 13: Normal distribution | Statistics 110
51:10
Lecture 14: Location, Scale, and LOTUS | Statistics 110
48:55
Lecture 15: Midterm Review | Statistics 110
38:12
Lecture 16: Exponential Distribution | Statistics 110
18:20
Lecture 17: Moment Generating Functions | Statistics 110
50:45
Lecture 18: MGFs Continued | Statistics 110
49:41
Lecture 19: Joint, Conditional, and Marginal Distributions | Statistics 110
50:09
Lecture 20: Multinomial and Cauchy | Statistics 110
49:00
Lecture 21: Covariance and Correlation | Statistics 110
49:26
【哈佛大学】中国（ChinaX） 【Part 7】【内嵌ass双语字幕】
5.0万播放
【What\'s this all about? (Optional)】Trailer
02:42
【Part 7 Introduction】Part 7 Introduction
12:13
【Myths and Lessons of Modern Chinese History】Historical Overview
06:36
【Myths and Lessons of Modern Chinese History】Section 1: Knowing What We Know-The End of an Imperial Tradition
03:40
【Myths and Lessons of Modern Chinese History】Section 1: Knowing What We Know-What We Know about China
03:51
【Myths and Lessons of Modern Chinese History】Section 1: Knowing What We Know-Viewing the Great Wall
03:06
【Myths and Lessons of Modern Chinese History】Section 2: Myth 1-1. Myth 1
06:52
【Myths and Lessons of Modern Chinese History】Section 2: Myth 1-2. Cultural Unity
03:37
【Myths and Lessons of Modern Chinese History】Section 3: Myth 2-Myth 2
04:00
【Myths and Lessons of Modern Chinese History】Section 4: Myth 3-Myth 3
08:45
【Achievement and Limits of Manchu Rule (Review)】Section 1: Ming and Manchu Memories-Ming and Manchu Memories
07:12
【Achievement and Limits of Manchu Rule (Review)】Section 2: Manchu Origins-Manchu Origins
07:56
【Achievement and Limits of Manchu Rule (Review)】Section 3: Conquering-Conquering
08:24
【Achievement and Limits of Manchu Rule (Review)】Section 4: The Rule of the Manchus-The Rule of the Manchus
05:52
【Achievement and Limits of Manchu Rule (Review)】Section 5: Presiding and Decreasing Success of the Qing Emperor-Presidin
07:08
【Opium and the Opium War】Section 1: The Chinese World Order-The Chinese World Order
04:13
【Opium and the Opium War】Section 1: The Chinese World Order-The Chinese Centrality in Foreign Relations
05:48
【Opium and the Opium War】Section 2: Opium and a Changing World Order-Mutual Addictions
04:25
【Opium and the Opium War】Section 2: Opium and a Changing World Order-The History of Opium
02:32
【Opium and the Opium War】Section 2: Opium and a Changing World Order-The Opium Trade
06:03
【Opium and the Opium War】Section 3: Effects of Opium and the Qing\'s Response-Economic Consequences of the Opium Trade
03:02
【Opium and the Opium War】Section 3: Effects of Opium and the Qing\'s Response-Commissioner Lin at Canton
09:19
【Opium and the Opium War】Section 4: The Aftermath of the Opium War-The Aftermath of the Opium War
05:25
【Christianity and Chinese Salvation】Music-Onward Christian Soldiers
01:51
【Christianity and Chinese Salvation】Section 1: Encountering the West-Encountering the West
03:57
【Christianity and Chinese Salvation】Section 2: Neiluan, Internal Turmoil-Neiluan, Internal Turmoil
01:59
【Christianity and Chinese Salvation】Section 2: Neiluan, Internal Turmoil-The Rise of Hong Xiuquan
03:58
【Christianity and Chinese Salvation】Section 2: Neiluan, Internal Turmoil-Taiping, The Age of Great Peace
04:58
【Christianity and Chinese Salvation】Section 3: Waihuan, External Disasters-Waihuan, External Disasters
05:15
【Christianity and Chinese Salvation】Section 3: Waihuan, External Disasters-The Western Missionary Movement
06:13
【Christianity and Chinese Salvation】Section 4: Massacres-The Fall of the Heavenly Kingdom
03:01
【Christianity and Chinese Salvation】Section 4: Massacres-Tianjin Massacre
03:23
【Christianity and Chinese Salvation】Section 4: Massacres-After the Massacre
01:37
【Fall of Imperial China】Section 1: The Fall of Imperial China-Introduction
02:06
【Fall of Imperial China】Section 1: The Fall of Imperial China-Leadership in the Late Qing
04:47
【Fall of Imperial China】Section 1: The Fall of Imperial China-The Western Threat
03:00
【Fall of Imperial China】Section 2: Self-Strengthening-Appropriating Western Technology
03:15
【Fall of Imperial China】Section 2: Self-Strengthening-Dangers of Western Learning
06:45
【Fall of Imperial China】Section 3: Resistance-Resistance of Reform
01:03
【Fall of Imperial China】Section 3: Resistance-Boxers and the Qing Response
04:48
【Fall of Imperial China】Section 4: Reform-Reform
06:10
HarvardX-Using Python for Research
1514播放
1.1.1 python basics
04:31
1.1.2 objects
04:40
1.1.3 modules and methods
07:30
1.1.4 numbers and basic calculations
04:27
1.1.5 random choice
01:56
1.1.6 expressions and booleans
05:52
1.2.1 sequences
03:23
1.2.2 lists
07:13
1.2.3 tuples
06:37
1.2.4 ranges
02:47
1.2.5 strings
08:39
1.2.6 sets
07:03
1.2.7 dictionaries
08:10
1.3.1 dynamic typing
11:26
1.3.2 copies
01:59
1.3.3 statements
04:36
1.3.4 for and while loops
08:06
1.3.5 list comprenensions
02:38
1.3.6 reading and writing files
05:21
1.3.7 introduction to functions
05:24
1.3.8 writing simple functions
09:37
1.3.9 common mistakes and errors
06:45
2.1.1 scope rules
08:30
2.1.2 classes and object-oriented programming
07:35
2.2.1 introduction to numpy arrays
06:27
2.2.2 slicing numpy arrays
05:14
2.2.3 indexing numpy arrays
07:22
2.2.4 building and examing numpy arrays
05:53
2.3.1 introduction to matplotlib and pyplot
08:22
2.3.2 customizing your plots
05:29
2.3.3 plotting using logarithmic axes
05:08
2.3.4 generating histograms
07:47
2.4.1 simulating randomness
07:42
2.4.2 examples involving randomness
13:41
2.4.3 using the numpy random module
11:37
2.4.4 measuring time
03:44
2.4.5 random walks
16:42
3.1.1 introduction to DNA translation
04:45
3.1.2 downloading DNA data
04:23
3.1.3 importting DNA data into python
04:58
3.1.4 translating the DNA sequence
12:27
3.2.1 introduction to language processing
02:17
4.1.1Getting started with pandas
11:04
4.1.2 loading and inspecting data
04:30
4.1.3 exploring correlations
05:39
4.1.4 clustering whiskies by flavor profile
06:56
4.1.5 comparing correlation matrices
04:00
4.2.1 introduction to gps tracking of birds
02:55
【古典乐赏析】First Nights - Beethoven's 9th（HarvardX） （英文字幕）
3766播放
01Lesson 1 Introduction - The Significance of Beethoven's 9th Symphony
04:44
02Lesson 1 Introduction Beethoven's Orchestra Instruments of the Orchestra
05:31
03Lesson 1 Introduction Beethoven's Orchestra Playing in an Orchestra
05:18
04Lesson 1 Introduction Beethoven's Orchestra Orchestral Scores
05:54
05Lesson 1 Introduction Beethoven's Vienna Beethoven's Vienna
06:54
06Lesson 2 What is a Symphony Pt. 1 - Movements
05:41
07Lesson 2 What is a Symphony Pt. 2 - Themes
11:11
08Lesson 2 What is a Symphony Pt. 3 Mozart's 40th Symphony as Template
08:14
09Lesson 2 What is a Symphony Overview of Beethoven's Ninth Symphony
07:58
10Lesson 2 What is a Symphony Overview of Beethoven's Ninth Symphony II
14:31
11Lesson 3 The Music - Pt. 1 I. Allegro ma non troppo Composing With motives
07:24
12Lesson 3 The Music - Pt. 1 I. Allegro ma non troppo(Live Demo)
09:42
13Lesson 3 The Music - Pt. 1 II. Scherzo
11:21
14Lesson 3 The Music - Pt. 1 III. Adagio molto e cantabile
11:41
15Lesson 4 The Music, Pt. 2 IV. The Finale Ode to Joy Schiller
03:44
16Lesson 4 The Music, Pt. 2 IV. The Finale Motives in the Finale
07:20
17Lesson 4The Music, Pt. 2 the Keys and Scales —D Major & D Minor
10:38
18Lesson 4 The Music, Pt. 2 the B-flat vs. B-natural
15:03
19Lesson 5 Preparations and Reception Finding a Theatre
09:00
20Lesson 5 Preparations and Reception The Program and the Performers
12:44
21Lesson 5 Preparations and Reception Setting the Stage
12:13
22Lesson 5 Preparations and Reception What was it like to be there
09:04
194播放
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