Python 初級 - 數據科學：NumPy入門教程|數據分析|Data Science|教學|廣東話 Video

Patreon: https://www.patreon.com/kfsoft
Doing data science with python:
1) Array creation & data type
2) ufunc: vectorized ops
3) basic manipulation
4) broadcast: vectorized ops on arrays with different shapes
Files: https://github.com/learn10kYear/learn-pandas/tree/master/numpy

00:00 Intro
01:47 Roadmap - 4 parts 1) Create 2) ufunc 3) manipulate 4) broadcast
03:29 Packages installation
05:09 Why numpy array
08:51 Numpy vs python's list - numpy is much faster
15:55 Pt1 - Basics - ndim, shape, dtype, strides
25:47 Pt1 - Pandas & numpy: df.to_numpy(), df.values
29:04 Pt1 - Create - 9 methods
29:52 Pt1 - Create - np.array(), np.arange()
22:43 Pt1 - Create - np.zeros(), np.ones(), np.empty()
35:09 Pt1 - Create - np.full(), np.eye(), np.identity()
36:21 Pt1 - Create - np.random.random(), np.random.randint(), np.linspace()
38:14 Pt1 - dtype - data types & type codes
39:27 Pt1 - dtype - type code - i1,i2,i4,i8 (intX)
41:58 Pt1 - dtype - type code - f2,f4,f8 (floatX)
42:19 Pt1 - dtype - type code - ? (bool) & O (object)
42:37 Pt1 - dtype - type code - S (string_) & U (unicode_)
45:26 Pt1 - dtype - specify the dtype when creating array
48:58 Pt1 - dtype - changing array dtype after creating array - astype()
50:40 Pt2 - ufunc - vectorized ops
51:39 Pt2 - ufunc - np.add(), np.substract()
54:20 Pt2 - ufunc - np.multiply(), np.divide(), np.square()
56:45 Pt2 - ufunc - universal functions, element-wise computations
56:45 Pt2 - ufunc - np.maximum()
59:03 Pt2 - ufunc - np.abs(), np.square(), np.sqrt()
01:00:22 Pt2 - ufunc - np.sin(), np.cos(), plot graph
01:02:35 Pt2 - ufunc - np.greater()
01:03:19 Pt2 - aggregate functions - np.mean(), np.sum(), np.max(), etc.
01:05:16 Pt2 - reduction - np.add.reduce() = np.sum()
01:06:40 Pt2 - accumulation - np.add.accumulate() = np.cumsum()
01:07:29 Pt2 - cumulative functions - np.cumsum(), np.comprod()
01:09:24 Pt3 - manipulate - index & slice (1d examples)
01:12:22 Pt3 - manipulate - update sliced view also update the original array
01:13:12 Pt3 - manipulate - copy()
01:14:06 Pt3 - manipulate - index & slice (2d examples)
01:18:17 Pt3 - manipulate - np.newaxis, increase dimension
01:19:56 Pt3 - manipulate - boolean mask
01:26:15 Pt3 - manipulate - sorting
01:28:24 Pt3 - manipulate - fancy index
01:29:41 Pt3 - manipulate - transpose - arr.T, arr.swapaxes()
01:30:39 Pt3 - manipulate - concatenate(axis=0), vstack(), row_stack()
01:33:16 Pt3 - manipulate - concatenate(axis=1), hstack(), column_stack()
01:34:32 Pt3 - manipulate - np.split()
01:38:57 Pt3 - manipulate - stack helpers - np.r_, np.c_
01:47:55 Pt3 - manipulate - File I/O - np.save(), np.savez_compressed(), np.load()
01:54:45 Pt3 - linear algebra - np.dot(), np.linalg.det(), np.linalg.inv()
01:56:32 Pt3 - linear algebra - np.diag(), np.linalg.solve()
01:58:17 Pt4 - broadcast - doing arithmetics with arrays in different shapes
02:01:39 Pt4 - broadcast - arrays in same size example - element-wise computations
02:03:02 Pt4 - broadcast - CASE 1: array and a scalar example - element-wise computations after stretching
02:07:16 Pt4 - broadcast - CASE 2: arrays in different shapes example - BROADCAST RULE - match trailing axes (1 or equal), PASS - expand and do vectorized ops
02:14:02 Pt4 - broadcast - CASE 2: BROADCAST RULE check fail - incompatible (value error)
02:15:29 Pt4 - broadcast - CASE 2: arrays in different shapes example - both arrays need stretching
02:21:15 Pt4 - broadcast - CASE 2: stretching is conceptual only, numpy don't do this in your main memory
02:25:24 Pt4 - broadcast - try more examples listed in numpy offical website
02:31:07 Summary & conclusion

Python入門：第1課 - PyCharm + Data Types https://youtu.be/s9toTBXQSPE
Python入門：第2課 - Python containers (1): List, Tuple https://youtu.be/7hm0zHgEGZ4
Python入門：第3課 - Python containers (2): Dictionary & Set https://youtu.be/7Jvfd6qFLzU
Python入門：第4課 - If-Else, Looping, Try-except https://youtu.be/sXdh5L5rcX0
Python入門：第5課 - Function + File https://youtu.be/rk8kU3no5No
Python入門：第6課 - Class and Object https://youtu.be/HPb0Lg3FQfM
Python入門：第7課 - URL, JSON, Sqlite https://youtu.be/93lOZTxJtrs
Python入門：第8課 - 用Flask進行Web開發 https://youtu.be/Z4CR3rwVkGc
Python入門：第9課 - Flask + DB ORM https://youtu.be/ZQoBdEH1zow
Python入門：第10課 - Flask補充1 https://youtu.be/AC23QWvFNWI
Python入門：第11課 - Flask補充2 https://youtu.be/-PkZ8sGhm-U

Python入門 - 數據科學 - Jupyter Lab & Notebook 安裝+入門教程 https://youtu.be/niWD8kxgpH0
Python入門 - 數據科學 - Anaconda + PyCharm 安裝 https://youtu.be/H4ihRvtdY7M
Python初級 - 數據科學 - Numpy入門 https://youtu.be/t7ygnafk760
Python初級 - 數據科學 - Pandas入門 https://youtu.be/ZYjhM7J9eFQ
Python初級 - 數據科學 - Pandas時間 + 圖表 https://youtu.be/jrd8shHEVFQ
Python初級 - 數據科學 - Pandas類別 + 樣式 https://youtu.be/4ntwbAWnKbg

Python初級 - 機器學習 - Scikit-learn 入門 https://youtu.be/3m8Bb01uNNE
Python初級 - 機器學習 - Scikit-learn - Regression 回歸 https://youtu.be/QyYZT8o-f3U
Python初級 - 機器學習 - Scikit-learn - Classification 分類 https://youtu.be/JKn0OoHSoRo
Python初級 - 機器學習 - Scikit-learn - Clustering 聚類+降維 https://youtu.be/UgXyK-k-CgM

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