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585B |
| 0 |
179.04KB |
| 001. Learn Enough Python to Be Dangerous Introduction.mp4 |
26.27MB |
| 001. Learn Enough Python to Be Dangerous Summary.mp4 |
11.52MB |
| 001. Topics.mp4 |
9.12MB |
| 001. Topics.mp4 |
9.04MB |
| 001. Topics.mp4 |
8.39MB |
| 001. Topics.mp4 |
5.19MB |
| 001. Topics.mp4 |
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| 001. Topics.mp4 |
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| 001. Topics.mp4 |
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| 001. Topics.mp4 |
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| 001. Topics.mp4 |
4.28MB |
| 001. Topics.mp4 |
4.25MB |
| 001. Topics.mp4 |
3.80MB |
| 002. 1.1 Introduction to Python.mp4 |
5.73MB |
| 002. 10.1 Setup.mp4 |
9.90MB |
| 002. 11.1 Data science setup.mp4 |
5.44MB |
| 002. 2.1 String basics.mp4 |
6.86MB |
| 002. 3.1 Splitting.mp4 |
4.69MB |
| 002. 4.1 Math.mp4 |
13.12MB |
| 002. 5.1 Function definitions.mp4 |
27.25MB |
| 002. 6.1 List comprehensions.mp4 |
10.48MB |
| 002. 7.1 Defining classes.mp4 |
12.81MB |
| 002. 8.1 Package setup.mp4 |
8.67MB |
| 002. 9.1 Reading from files.mp4 |
24.13MB |
| 003. 1.2 Python in a REPL.mp4 |
2.26MB |
| 003. 10.2 Site pages.mp4 |
13.50MB |
| 003. 11.2 Numerical computations with NumPy.mp4 |
30.95MB |
| 003. 2.2 Concatenation and interpolation.mp4 |
9.45MB |
| 003. 3.2 List access.mp4 |
4.48MB |
| 003. 4.2 Times and datetimes.mp4 |
13.41MB |
| 003. 5.2 Functions in a file.mp4 |
12.13MB |
| 003. 6.2 List comprehensions with conditions.mp4 |
10.29MB |
| 003. 7.2 Custom iterators.mp4 |
10.57MB |
| 003. 8.2 Initial test coverage.mp4 |
31.41MB |
| 003. 9.2 Reading from URLs.mp4 |
14.06MB |
| 004. 1.3 Python in a file.mp4 |
9.22MB |
| 004. 10.3 Layouts.mp4 |
41.89MB |
| 004. 11.3 Data visualization with Matplotlib.mp4 |
42.71MB |
| 004. 2.3 Printing.mp4 |
3.58MB |
| 004. 3.3 List slicing.mp4 |
7.96MB |
| 004. 4.3 Regular expressions.mp4 |
13.49MB |
| 004. 5.3 Iterators.mp4 |
21.75MB |
| 004. 6.3 Dictionary comprehensions.mp4 |
7.98MB |
| 004. 7.3 Inheritance.mp4 |
8.46MB |
| 004. 8.3 Red.mp4 |
16.20MB |
| 004. 9.3 DOM manipulation at the command line.mp4 |
34.54MB |
| 005. 1.4 Python in a shell script.mp4 |
4.63MB |
| 005. 10.4 Template engine.mp4 |
30.17MB |
| 005. 11.4 Introduction to data analysis with pandas.mp4 |
19.45MB |
| 005. 2.4 Length, booleans, and control flow.mp4 |
18.03MB |
| 005. 3.4 More list techniques.mp4 |
13.25MB |
| 005. 4.4 Dictionaries.mp4 |
17.00MB |
| 005. 6.4 Generator and set comprehensions.mp4 |
6.00MB |
| 005. 7.4 Derived classes.mp4 |
23.13MB |
| 005. 8.4 Green.mp4 |
18.91MB |
| 006. 1.5 Python in a web browser.mp4 |
22.17MB |
| 006. 10.5 Palindrome detector.mp4 |
62.78MB |
| 006. 11.5 pandas example Nobel laureates.mp4 |
62.82MB |
| 006. 2.5 Methods.mp4 |
10.59MB |
| 006. 3.5 List iteration.mp4 |
4.67MB |
| 006. 4.5 Application Unique words.mp4 |
18.69MB |
| 006. 6.5 Other functional techniques.mp4 |
7.44MB |
| 006. 8.5 Refactor.mp4 |
30.51MB |
| 007. 10.6 Conclusion.mp4 |
1.90MB |
| 007. 11.6 pandas example Titanic.mp4 |
27.64MB |
| 007. 2.6 String iteration.mp4 |
9.61MB |
| 007. 3.6 Tuples and sets.mp4 |
8.49MB |
| 008. 11.7 Machine learning with scikit-learn.mp4 |
44.11MB |
| 009. 11.8 Further resources and conclusion.mp4 |
1.64MB |
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| TutsNode.net.txt |
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