[Lynda] NumPy Data Science Essential Training

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[CourseClub.NET] Lynda - NumPy Data Science Essential Training
  • 01-Welcome.en.srt (1.1 KB)
  • 01-Welcome.mp4 (5.9 MB)
  • 02-What you should know.en.srt (0.6 KB)
  • 02-What you should know.mp4 (607.0 KB)
  • 03-NumPy, data science, IMQAV.en.srt (8.5 KB)
  • 03-NumPy, data science, IMQAV.mp4 (12.9 MB)
  • 04-How to use the exercise files.en.srt (3.1 KB)
  • 04-How to use the exercise files.mp4 (3.7 MB)
  • 05-Install software.en.srt (3.0 KB)
  • 05-Install software.mp4 (5.5 MB)
  • 06-Introduction to Jupyter Notebook.en.srt (4.6 KB)
  • 06-Introduction to Jupyter Notebook.mp4 (9.1 MB)
  • 07-Notebook basics.en.srt (12.8 KB)
  • 07-Notebook basics.mp4 (21.0 MB)
  • 08-Markdown.en.srt (6.2 KB)
  • 08-Markdown.mp4 (11.5 MB)
  • 09-Beautiful mathematics typesetting.en.srt (4.5 KB)
  • 09-Beautiful mathematics typesetting.mp4 (10.5 MB)
  • 10-Launch Jupyter Notebook.en.srt (3.0 KB)
  • 10-Launch Jupyter Notebook.mp4 (5.0 MB)
  • 11-Create arrays from Python structures.en.srt (10.3 KB)
  • 11-Create arrays from Python structures.mp4 (17.7 MB)
  • 12-Intrinsic creation using NumPy methods.en.srt (10.5 KB)
  • 12-Intrinsic creation using NumPy methods.mp4 (17.7 MB)
  • 13-linspace, zeros, ones, data types.en.srt (14.0 KB)
  • 13-linspace, zeros, ones, data types.mp4 (24.1 MB)
  • 14-Slice arrays.en.srt (10.6 KB)
  • 14-Slice arrays.mp4 (18.1 MB)
  • 15-Boolean mask arrays.en.srt (6.9 KB)
  • 15-Boolean mask arrays.mp4 (12.0 MB)
  • 16-Broadcasting.en.srt (16.1 KB)
  • 16-Broadcasting.mp4 (30.0 MB)
  • 17-Structured and record arrays.en.srt (15.0 KB)
  • 17-Structured and record arrays.mp4 (27.7 MB)
  • 18-Inline plotting.en.srt (4.0 KB)
  • 18-Inline plotting.mp4 (6.6 MB)
  • 19-Figures and subplots.en.srt (7.0 KB)
  • 19-Figures and subplots.mp4 (13.0 MB)
  • 20-Multiple lines, single plot.en.srt (9.2 KB)
  • 20-Multiple lines, single plot.mp4 (16.5 MB)
  • 21-Tick marks, labels, and grids.en.srt (4.8 KB)
  • 21-Tick marks, labels, and grids.mp4 (8.2 MB)
  • 22-Plot annotations.en.srt (7.1 KB)
  • 22-Plot annotations.mp4 (13.9 MB)
  • 23-Pie charts and bar charts.en.srt (5.8 KB)
  • 23-Pie charts and bar charts.mp4 (11.6 MB)
  • 24-Beautiful plots, the gallery.en.srt (6.4 KB)
  • 24-Beautiful plots, the gallery.mp4 (12.1 MB)
  • 25-Views and copies.en.srt (10.9 KB)
  • 25-Views and copies.mp4 (19.1 MB)
  • 26-Array attributes.en.srt (2.1 KB)
  • 26-Array attributes.mp4 (4.0 MB)
  • 27-Add and remove elements.en.srt (12.2 KB)
  • 27-Add and remove elements.mp4 (23.1 MB)
  • 28-Join and split arrays.en.srt (9.4 KB)
  • 28-Join and split arrays.mp4 (19.1 MB)
  • 29-Array shape manipulation.en.srt (6.3 KB)
  • 29-Array shape manipulation.mp4 (11.3 MB)
  • 30-Rearrange array elements.en.srt (6.4 KB)
  • 30-Rearrange array elements.mp4 (12.9 MB)
  • 31-Transpose like operations.en.srt (5.8 KB)
  • 31-Transpose like operations.mp4 (11.6 MB)
  • 32-Tiling arrays.en.srt (4.7 KB)
  • 32-Tiling arrays.mp4 (9.5 MB)
  • 33-Universal functions.en.srt (6.4 KB)
  • 33-Universal functions.mp4 (12.8 MB)
  • 34-Pythagorean triangles.en.srt (5.4 KB)
  • 34-Pythagorean triangles.mp4 (8.3 MB)
  • 35-Linear algebra.en.srt (11.4 KB)
  • 35-Linear algebra.mp4 (19.6 MB)
  • 36-Finding patterns.en.srt (12.0 KB)
  • 36-Finding patterns.mp4 (19.3 MB)
  • 37-Statistics.en.srt (11.8 KB)
  • 37-Statistics.mp4 (20.4 MB)
  • 38-Brain teasers.en.srt (17.2 KB)
  • 38-Brain teasers.mp4 (29.8 MB)
  • 39-Magic squares and NumPy.en.srt (9.4 KB)
  • 39-Magic squares and NumPy.mp4 (19.5 MB)
  • 40-Adjacency matrix.en.srt (8.8 KB)
  • 40-Adjacency matrix.mp4 (16.7 MB)
  • 41-Magic characteristics.en.srt (7.5 KB)
  • 41-Magic characteristics.mp4 (15.1 MB)
  • 42-Build magic cubes.en.srt (5.0 KB)
  • 42-Build magic cubes.mp4 (10.2 MB)
  • 43-Next steps.en.srt (1.5 KB)
  • 43-Next steps.mp4 (2.4 MB)
  • [CourseClub.NET].url (0.1 KB)
  • [FreeCourseSite.com].url (0.1 KB)

Description



[Lynda] NumPy Data Science Essential Training

NumPy Data Science Essential Training introduces the beginning to intermediate data scientist to NumPy, the Python library that supports numerical, scientific, and statistical programming, including machine learning. The library supports several aspects  of data science, providing multidimensional array objects, derived objects (matrixes and masked arrays), and routines for math, logic, sorting, statistics, and random number generation. Here Charles Kelly shows how to work with NumPy and Python within Jupyter Notebook, a browser-based tool for creating interactive documents with live code, annotations, and even visualizations such as plots.



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[Lynda] NumPy Data Science Essential Training

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Download torrent
600.2 MB
seeders:7
leechers:2
[Lynda] NumPy Data Science Essential Training

Torrent hash: 268F39D10D7A6128C390C533DE5532BB477061AF