Data Science Prerequisites - Numpy, Matplotlib, and Pandas in Python

1.02 GB | 00:14:49 | mp4 | 1920X1080 | 16:9
Genre:eLearning |Language:English

Files Included :
001 Introduction and Outline (43.24 MB)
002 Course Resources (16.15 MB)
001 NumPy Section Introduction (17.77 MB)
002 Arrays Versus Lists (37.93 MB)
003 Dot Product (21.33 MB)
004 Speed Test (13.52 MB)
005 Matrices (42.73 MB)
006 Solving Linear Systems (13.62 MB)
007 Generating Data (47.79 MB)
008 NumPy Exercise (5.98 MB)
009 Where to Learn More NumPy (31.18 MB)
010 Suggestion Box (17.35 MB)
001 Matplotlib Section Introduction (13.59 MB)
002 Line Chart (13.64 MB)
003 Scatterplot (15.38 MB)
004 Histogram (10.1 MB)
005 Plotting Images (27.73 MB)
006 Matplotlib Exercise (11.37 MB)
007 Where to Learn More Matplotlib (53.25 MB)
001 Pandas Section Introduction (7.8 MB)
002 Loading in Data (18.69 MB)
003 Selecting Rows and Columns (33.98 MB)
004 The apply() Function (10.55 MB)
005 Plotting with Pandas (11.37 MB)
006 Pandas Exercise (12.86 MB)
007 Where to Learn More Pandas (20.28 MB)
001 SciPy Section Introduction (8.5 MB)
002 PDF and CDF (12.16 MB)
003 Convolution (17.26 MB)
004 SciPy Exercise (7.81 MB)
005 Where to Learn More SciPy (28.3 MB)
001 Machine Learning Section Introduction (33.59 MB)
002 What Is Classification (49.77 MB)
003 Classification in Code (81 MB)
004 What Is Regression (37.88 MB)
005 Regression in Code (41.5 MB)
006 What Is a Feature Vector (27.65 MB)
007 Machine Learning Is Nothing but Geometry (18.05 MB)
008 All Data Is the Same (19.43 MB)
009 Comparing Different Machine Learning Models (38.1 MB)
010 Machine Learning and Deep Learning Future Topics (31.2 MB)
011 Machine Learning Section Summary (20.3 MB)]
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