10 היכרות עם המרצה2:37
27.0 data analysis visualization- introduction18:52
37.1.1 jupyter_conda- jupyter notebook19:27
47.1.2 - jupyter_conda - conda20:35
57.2.1 statistics - types of data9:14
67.2.2 statistics - basic statistic21:59
77.2.3 statistic - probability18:56
87.2.4 statistics - probability distributions20:28
97.3.1 data generation - intoduction21:41
107.3.2 data generation - challenges20:58
117.3.3 data generation - strategies21:13
127.4.1 pandas - introduction21:05
137.4.2 pandas - selections20:04
147.4.3 pandas - operations20:59
157.4.4 pandas - exercises21:14
167.5.1 vectors - introduction12:58
177.5.2 vectors - vector operations21:18
187.5.3 vectors - linear transformations and norm20:27
197.6.1 matrices - introduction21:35
207.6.2 matrices - matrices multiplication21:37
217.6.3 matrices - properties of matrices multiplication20:00
227.6.4 matrices - transpose identity and inverse21:08
237.7.1 linear algebra - determinant17:57
247.7.2 linear algebra - eigenvalues and eigenvectors15:11
257.7.3 linear algebra - system of equations21:56
267.8.1 numpy - introduction19:23
277.8.2 numpy - basic operations20:27
287.8.3 numpy - indexing and iterating21:58
297.8.4 numpy - shape manipulations21:06
307.8.5 numpy - boolean indexing17:36
317.9 scipy19:57
327.10.1 visualization using matplotlib20:09
337.10.2 visualization using matplotlib - pie chart8:11
347.11 visualization using seaborn17:42
357.12.1 MongoDB - introduction and installation17:49
367.12.2 MongoDB - CRUD queries21:55
377.12.3 MongoDB - aggregations part A21:44
387.12.4 MongoDB - aggregations part B19:47
397.12.5 MongoDB - search and visualization9:42
407.12.6 MongoDB - exercises part A22:32
417.12.7 MongoDB - exercises part B15:58
