Complete scipy masterclass go from zero to hero in scipy
Indexed public MEGA.nz folder containing 122 files across 26 folders, with a total indexed size of 4.6 GB. Last scan: Sep 29, 2026.
Indexed contents
122 files in 26 folders
Files
- must read.txt
- 4. numpy constants.mp4
- 5. numpy datatypes.html
- 6. image statistics.mp4
- 1. course objectives.mp4
- 1. bitwise operations.mp4
- 1. constants in scipy.mp4
- 1. k-means clustering.mp4
- 3. ndarray properties.mp4
- 1. ipython and jupyter.mp4
- 1. what is pypi and pip.mp4
- 1. what is raspberry pi.mp4
- 2. raspberry pi unboxing.mp4
- 9. arithmetic operations.mp4
- 1. hello world on windows.mp4
- 8. python on raspberry pi.mp4
- 6. a brief tour of jupyter.mp4
- 4. install putty on windows.mp4
- 1. audio processing in scipy.mp4
- 2. course content walkthrough.mp4
- 3. introduction to matplotlib.mp4
- 1. convolution and correlation.mp4
- 2. hello world on raspberry pi.mp4
- 2. image datasets for practice.mp4
- 4. scientific python ecosystem.mp4
- 1. one dimensional ffts and ifft.mp4
- 1. statistical functions in numpy.mp4
- 2. ndarray, indexing, and slicing.mp4
- 7. commands used in this section.html
- 2. jupyter installation on windows.mp4
- 1. what is digital image processing.mp4
- 1. routines for ndarray manipulation.mp4
- 3. python interpreter vs script mode.mp4
- 4. numerical ranges and visualizations.mp4
- 3. jupyter installation on raspberry pi.mp4
- 2. installation of scipy on raspberry pi.mp4
- 3. please do leave your valuable feedback.mp4
- 1. install numpy and matplotlib on windows.mp4
- 1. python code files and jupyter notebook.html
- 1. creating numpy arrays with random elements.mp4
Showing a summary of 40 out of 122 files.
Folders
- complete scipy masterclass go from zero to hero in scipy
- ipynb_checkpoints
- codebundle
- 1. introduction
- 2. install python 3 on windows
- 3. python 3 and raspberry pi
- 4. python basics
- 5. python package index and pip
- 6. numpy and matplotlib installation on windows and raspberry pi
- 7. jupyter
- 8. introduction to numpy
- 9. creating and visualizing numpy arrays
- 10. random sampling
- 11. ndarray manipulation
- 12. bitwise operations
- 13. statistical functions in numpy
- 14. installation of scipy on windows pc and raspberry pi
- 15. getting started with scipy with constants and linear algebra
- 16. integration
- 17. signal processing
Showing a summary of 20 out of 26 folders.
Content summary
- Videos
- 71
- Archives
- 1
- Documents
- 17
- Others
- 33