NumPy, Pandas and Matplotlib A-Z™ for Machine Learning 2024

Focused View

Donatus Obomighie | PhD, MSc, PMP

11:31:44

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1. NumPy - Setups

1. Course Syllabus Walkthrough.mp4

04:16

2. Installing Jupiter Notebook.mp4

01:50

3. Installing of NumPy.mp4

00:29

4. Importing NumPy.mp4

00:29

2. NumPy - Introduction

1. What is NumPy.mp4

01:33

2. What is Arrray.mp4

02:11

3. Types of Array.mp4

00:53

4. What is Dimension.mp4

04:24

5. Exploring - Row Before Column - Why.mp4

09:13

6. Identifying an Array.mp4

07:21

7. Scalar vs Vector vs Matrix vs Tensor.mp4

06:07

3. NumPy - Creating Arrays

1. First Time Creating an Array.mp4

01:31

2. Creating an Array from a Tuple.mp4

00:55

3. Creating a Zero Dimensional Array.mp4

03:30

4. Avoiding Errors of Multiple Arguments.mp4

02:53

5. Creating a 1-D Array.mp4

00:41

6. Creating a 2-D Array.mp4

01:04

7. Creating a 3-D Array.mp4

02:58

4. NumPy - Data Type

1. Understanding NumPy Data Type.mp4

09:15

2. Forcing a Data Type of an Array.mp4

04:47

5. NumPy - Challenges and Solution - Creating Arrays

1. The Challenges.mp4

01:06

2. The Challenges - text.html

3. Solution to Challenge 1a.mp4

00:40

4. Solution to Challenge 1b.mp4

01:14

5. Solution to Challenge 1c.mp4

02:09

6. Solution to Challenge 1d.mp4

02:02

7. Solution to Challenge 1e.mp4

01:24

8. Solution to Challenge 2a.mp4

00:25

9. Solution to Challenge 2b.mp4

00:30

10. Solution to Challenge 2c.mp4

03:01

11. Solution to Challenge 2d.mp4

00:53

12. Solution to Challenge 2e.mp4

00:47

13. Solution to Challenge 2f.mp4

01:08

6. NumPy - Creating Arrays - (Others)

1. Array of Zeros.mp4

02:55

2. Arrays of Ones.mp4

00:56

3. Empty Arrays.mp4

00:57

4. How to use arange().mp4

02:47

5. How to use linspace().mp4

03:13

6. How to use reshape().mp4

01:55

7. NumPy - Attributes of an Array

1. How to find the attributes of an Array - (ndim, shape, size, dtype, itemsize).mp4

05:46

8. NumPy - Challenges and Solutions - Creating Arrays (More)

1. The Challenges.mp4

00:21

2. The Challenges - Text.html

3. Solution to Challenge 1a.mp4

02:56

4. Solution to Challenge 1b.mp4

00:58

5. Solution to Challenge 1c.mp4

01:19

6. Solution to Challenge 2a.mp4

01:09

7. Solution to Challenge 2b.mp4

01:09

8. Solution to Challenge 2c.mp4

00:51

9. Solution to Challenge 2d.mp4

00:31

10. Solution to Challenge 2e.mp4

00:54

11. Solution to Challenge 2f.mp4

00:45

12. Solution to Challenge #3.mp4

01:11

13. Solution to Challenge #4.mp4

04:03

9. NumPy - Array Sorting and Concatenation

1. Array Sorting.mp4

00:46

2. Array Concatenation.mp4

03:33

10. NumPy - 1-D Array Indexing and Slicing

1. Understanding how indexing and Slicing work on 1-D Arrays.mp4

12:34

11. NumPy - Challenges and Solution - 1-D Array Indexing & Slicing

1. The Challenges.mp4

00:21

2. The Challenges - Text.html

3. Solution to Challenge 1a.mp4

00:59

4. Solution to Challenge 1b.mp4

00:29

5. Solution to Challenge 1c.mp4

00:42

6. Solution to Challenge 1d.mp4

01:07

7. Solution to Challenge 1e.mp4

00:38

8. Solution to Challenge 1f.mp4

00:51

9. Solution to Challenge 1g.mp4

01:14

10. Solution to Challenge 1h.mp4

01:20

11. Solution to Challenge 1i.mp4

00:29

12. Solution to Challenge 1j.mp4

01:12

13. Solution to Challenge 1k.mp4

00:23

14. Solution to Challenge 1l.mp4

00:32

15. Solution to Challenge 1m.mp4

00:17

12. NumPy - Creating an Array from Existing Array

1. With Less Than, Greater Than or Equal To.mp4

00:30

2. Even and Odd Numbers.mp4

01:03

3. Two Conditions.mp4

02:57

13. NumPy - Challenges and Solutions - Creating an Array from Existing Array

1. The Challenges.mp4

00:33

2. The Challenges - Text.html

3. Solution to Challenge #1.mp4

00:28

4. Solution to Challenge #2.mp4

00:28

5. Solution to Challenge #3.mp4

00:31

6. Solution to Challenge #4.mp4

00:36

7. Solution to Challenge #5.mp4

01:48

14. NumPy - 2-D Array Indexing and Slicing

1. Selecting Elements of 2-D Array.mp4

01:13

2. Slicing In 2-D Array.mp4

04:17

15. NumPy - Challenges and Solution - 2-D Array Indexing & Slicing

1. The Challenges.mp4

00:15

2. The Challenges - Text.html

3. Solution to Challenge #1.mp4

00:30

4. Solution to Challenge #2.mp4

00:09

5. Solution to Challenge #3.mp4

00:59

6. Solution to Challenge #4.mp4

00:48

7. Solution to Challenge #5.html

8. Solution to Challenge #6.mp4

00:20

9. Solution to Challenge #7.mp4

01:10

16. NumPy - 3D Indexing and Slicing

1. Selecting Elements of 3-D Array.mp4

02:34

2. Slicing a 3-D Array.mp4

02:49

3. More on Slicing.mp4

07:01

17. NumPy - Challenges and Solution - 3-D Array Indexing & Slicing

1. The Challenges.mp4

00:27

2. The Challenges - Text.html

3. Solution to Challenge #1.mp4

01:00

4. Solution to Challenge #2.mp4

00:28

5. Solution to Challenge #3.mp4

00:58

6. Solution to Challenge #4.mp4

01:45

7. Solution to Challenge #5.mp4

01:36

8. Solution to Challenge #6.mp4

00:51

9. Solution to Challenge #7.mp4

03:02

10. Solution to Challenge #8.mp4

00:54

11. Solution to Challenge #9.mp4

00:44

12. Solution to Challenge #10.mp4

02:08

13. Solution to Challenge #11.mp4

02:51

14. Solution to Challenge #12.mp4

00:54

15. Solution to Challenge #13.mp4

00:35

16. Solution to Challenge #14.mp4

01:08

17. Solution to Challenge #15.mp4

00:56

18. Solution to Challenge #16.mp4

01:39

19. Solution to Challenge #17.mp4

00:42

18. NumPy - Summary - Selecting Element From Any n-D Array

1. Summary on Selecting Element From any Dimensional Array.mp4

04:51

19. NumPy - Array Flatten and Ravel

1. Understanding Array Flatten and Ravel.mp4

03:55

20. NumPy - Transpose

1. Understanding Array Transpose.mp4

01:17

21. NumPy - Reverse

1. Understanding How to Reverse an Array.mp4

01:53

2. Understanding How to Reverse Along an Axis.mp4

02:02

22. NumPy - Unique Array

1. Creating a Unique Array.mp4

00:42

2. Indexing a Unique Array.mp4

01:03

23. NumPy - Maximum, Minimum and Sum of an Array

1. Minimum, Maximum & Sum.mp4

00:35

2. Minimum, Maximum and Sum Along an Axis.mp4

02:17

24. NumPy - Stacking

1. Array Stacking.mp4

01:28

25. NumPy - Splitting an Array

1. Splitting an Array.mp4

04:04

2. Splitting an Array on a Specific Column.mp4

02:09

26. NumPy - Copying an Array

1. Understand how to Copy an Array.mp4

03:17

2. Understand how to Copy an Array II.mp4

02:41

27. NumPy - Array Operators

1. Understanding Array Operators.mp4

02:38

28. NumPy - Deleting Elements

1. How to delete Array Element I.mp4

02:36

2. How to delete Array Element II.mp4

01:59

3. Challenge & Solution I.mp4

00:58

4. Challenge & Solution II.mp4

00:39

5. Challenge & Solution III.mp4

00:39

6. Challenge & Solution III - Code.html

7. Challenge Yourself.html

8. Solution - Challenge Yourself.html

29. NumPy - Appending and Inserting Elements Into an Array

1. How to append & Insert an Element Into An Array.mp4

03:15

2. How to append & Insert Elements Into An Array.mp4

01:04

30. NumPy - Newaxis

1. Understanding Newaxis.mp4

05:05

31. NumPy - Trigonometric Function

1. Understanding NumPy Trigonometric Function.mp4

03:17

2. Understanding NumPy Trigonometric Function.html

32. NumPy - Searching Array

1. Understanding How to Search an Array.mp4

01:22

33. NumPy - Array Multiplication

1. Array Multiplication by a Single Number.mp4

01:06

2. Understanding dot().mp4

02:38

3. Challenge & Solution.mp4

01:34

34. NumPy - Trace

1. Understanding Trace.mp4

00:38

2. Challenge & Solution.mp4

00:35

35. NumPy - Outer Product

1. Understanding Outer Product.mp4

02:04

2. Challenge & Solution.mp4

00:46

36. NumPy - Inner Product

1. Understanding Inner Product.mp4

01:37

37. NumPy - Cross Product

1. Understanding Cross Product.mp4

01:10

2. Challenge & Solution - I.mp4

01:17

3. Challenge & Solution - II.mp4

03:07

38. NumPy - Kronecker Product

1. Understanding Kronecker Product.mp4

02:46

39. NumPy - Determinant

1. Understanding Determinant.mp4

02:55

2. Challenge & Solution - 2 by 2.mp4

00:49

3. Challenge & Solution - 3 by 3.mp4

02:21

40. NumPy - Inverse of Array

1. Understanding Inverse of Array.mp4

03:34

2. Challenge & Solution.mp4

00:19

41. NumPy - Condition Number

1. Understanding the Condition Number.mp4

02:05

42. NumPy - Random Sub-Module

1. Random Number (Integer).mp4

03:17

2. Random Number (Float).mp4

00:26

3. Random Arrays.mp4

03:22

4. Random Choice.mp4

00:52

5. Choice with 2-D and 3-D Array.mp4

01:23

43. NumPy - Seed

1. Understanding Random Seed.mp4

04:48

2. Random Seed With Choice().mp4

02:56

44. NumPy - Data Distribution

1. What is Data Distribution.mp4

01:26

2. What is Random Distribution.mp4

06:24

3. Random Distribution 2-D and 3-D Array.mp4

00:58

45. NumPy - Data Visualisation

1. NumPy vs MatPlotLib vs Seaborn.mp4

02:40

2. Installation of MatPlotLib and Seaborn.mp4

01:28

3. Challenge & Solution 1.mp4

04:05

4. Challenge & Solution II.mp4

00:30

46. NumPy - Normal Distribution & Visualisation

1. What is Normal Distribution.mp4

04:16

2. Normal Distribution Visualisation.mp4

02:05

47. NumPy - Binomial Distribution

1. Binomial Distribution.mp4

02:22

2. Binomial Data Visualisation.mp4

01:41

48. Pandas - Intro, Installation & DataFrame

1. Pandas Introduction.mp4

01:57

2. Pandas Installation & Import.mp4

00:43

3. Pandas DataFrame.mp4

02:12

49. Resources Used for Pandas

1.1 world-happiness-report.csv

1. Happiness Data Set.html

2.1 Sales data.csv

2. Sales Data Set.html

3.1 northwind data set.zip

3. Northwind Database.html

4.1 cities.csv

4. Cities Data Set.html

50. Pandas - Series

1. Understanding Pandas Series.mp4

01:07

51. Pandas - Label

1. Understanding Pandas Label.mp4

01:27

2. Creating Series From Dictionary.mp4

01:20

52. Pandas - DataFrame

1. Introduction to DataFrame in Pandas.mp4

02:01

2. Loc.mp4

00:58

3. Challenge & Solution.mp4

00:49

53. Pandas - Concatenation

1. Pandas - Understanding Concat in Pandas.mp4

03:56

2. Pandas - Understanding Concat in Pandas - Code.html

3. Pandas - Adding Hierarchy.mp4

00:56

4. Pandas - Adding Hierarchy - Code.html

5. Pandas - Concat Label.mp4

01:13

6. Pandas - Concat Label - Code.html

7. Pandas - Challenge & Solution.mp4

01:05

8. Pandas - Challenge & Solution - Code.html

9. Pandas - Concat Columns of Different Sizes.mp4

01:53

10. Pandas - Concat Columns of Different Sizes - Code.html

11. Pandas - Concat along axis.mp4

02:23

12. Pandas - Concat along axis - Code.html

54. Pandas - Merge

1. Pandas - Understanding Merge.mp4

01:46

2. Pandas - Understanding Merge - Code.html

3. Pandas - Merging DataFrame of Different Sizes.mp4

01:35

4. Pandas - Merging DataFrame of Different Sizes - Code.html

5. Pandas - Inner, Outer, Left and Right Join.mp4

05:08

6. Pandas - Inner, Outer, Left and Right Join - Code.html

7. Pandas - Merge Suffix.mp4

02:38

8. Pandas - Merge Suffix - Code.html

55. Pandas - Load CSV

1. Load CSV in Pandas.mp4

02:37

56. Pandas - Aggregate & Statistics (Min, Max, Sum, Mean, Median, Mode, Summary)

1. Pandas - Minimum and Maximum.mp4

00:40

2. Pandas - Minimum and Maximum - Singapore.mp4

01:26

3. Pandas - Mean, Median & Mode.mp4

00:51

4. Pandas - Mean, Median & Mode - Mexico.mp4

01:07

5. Pandas - Sum.mp4

01:08

6. Challenge & Solution.mp4

01:24

7. Pandas - Statistical Summary.mp4

01:15

8. Pandas - Count.mp4

00:57

57. Pandas - JSON

1. Pandas - Load JSON.mp4

02:21

58. Pandas - Challenges & Solutions

1. 1 - Pandas Challenge & Solution - Import.mp4

01:54

2. 2 - Pandas Challenge & Solution - Data Set Inspection - Shape, DataType & Column.mp4

01:27

3. 3 - Challenge & Solution - Skip Rows Reading CSV File.mp4

01:25

4. 3 - Challenge & Solution - Skip Rows Reading CSV File - Code.html

5. 4 - Challenge & Solution - Skip Rows Keep Headers.mp4

02:58

6. 4 - Challenge & Solution - Skip Rows Keep Headers - Code.html

7. 5 - Challenge & Solution - Read CSV Without Header.mp4

01:12

8. 5 - Challenge & Solution - Read CSV Without Header - Code.html

9. 6 - Challenge & Solution - Subset of Column.mp4

02:36

10. 6 - Challenge & Solution - Subset of Column - Code.html

11. 7 - Challenge & Solution - Few Rows.mp4

00:37

12. 7 - Challenge & Solution - Few Rows - Code.html

13. 8 - Challenge & Solution - Few Rows, Few Columns.mp4

00:50

14. 8 - Challenge & Solution - Few Rows, Few Columns - Code.html

15. 9 - Challenge & Solution - Time to Import.mp4

00:40

16. 9 - Challenge & Solution - Time to Import- Code.html

17. 10 - Challenge & Solution - Changing Data Type.mp4

01:42

18. 10 - Challenge & Solution - Changing Data Type - Code.html

59. Pandas - Challenges & Solutions

1. Pandas - Summary of Data Set.mp4

01:35

2. Pandas - Summary of Data Set - Code.html

3. Pandas - Subset of Column.mp4

01:53

4. Pandas - Subset of Column - Code.html

5. Pandas - Total number of Columns and Rows.mp4

02:18

6. Pandas - Total number of Columns and Rows - Code.html

7. Pandas - Last Ten Rows.mp4

00:52

8. Pandas - Last Ten Rows - Code.html

60. Pandas - Challenges & Solutions

1. Pandas - Difference between Loc and iloc.mp4

03:50

2. Pandas - Difference between Loc and iloc - more.mp4

07:52

3. Pandas - Difference between head and tail.mp4

01:30

4. Pandas - Difference between head and tail - Code.html

5. Pandas - Using Head, Loc & iLoc to Achieve the Same Result.mp4

00:51

6. Pandas - Using Head, Loc & iLoc to Achieve the Same Result - Code.html

7. Pandas - Using tail, loc and iloc for last row.mp4

02:43

8. Pandas - Using tail, loc and iloc for last row - Code.html

61. Pandas - Challenges & Solutions

1. Pandas - iloc & loc.mp4

05:10

2. Pandas - iloc & loc - code.html

3. Pandas - Without Using Tail or iLoc Get Last Row.mp4

03:15

4. Pandas - Without Using Tail or iLoc Get Last Row - Code.html

5. Pandas - Using Range.mp4

02:48

6. Pandas - Using Range - Code.html

7. Pandas - Another Selection Trick.mp4

02:32

8. Pandas - Another Selection Trick - Code.html

62. Pandas - Challenges & Solutions

1. Pandas - Even Columns.mp4

03:00

2. Pandas - Even Columns - Code.html

3. Pandas - Even Columns Without Using Range.mp4

04:30

4. Pandas - Even Columns Without Using Range - Code.html

5. Pandas - Specific Row.mp4

02:05

6. Pandas - Specific Row - Code.html

7. Pandas - Column.mp4

00:17

8. Pandas - Column - Code.html

9. Pandas - Filtering Greater Than.mp4

01:12

10. Pandas - Filtering Greater Than - Code.html

11. Pandas - Filtering Greater Than with Fewer Rows.mp4

01:02

12. Pandas - Filtering Greater Than with Fewer Rows - Code.html

63. Pandas - Challenges & Solutions

1. Pandas - nlargest.mp4

02:16

2. Pandas - nlargest - Code.html

3. Pandas - nsmallest.mp4

01:22

4. Pandas - nsmallest - Code.html

5. Pandas - Sort Values Ascending.mp4

01:52

6. Pandas - Sort Values Ascending - Code.html

7. Pandas - Sort Values for Smallest.mp4

01:46

8. Pandas - Sort Values for Smallest - Code.html

9. Pandas - Selecting a range of values.mp4

01:54

10. Pandas - Selecting a range of values - Code.html

11. Pandas - Return Random Rows.mp4

02:21

12. Pandas - Return Random Rows - Code.html

64. Pandas - Challenges & Solutions

1. Pandas - Reset Index.mp4

02:00

2. Pandas - Reset Index - Code.html

3. Pandas - Greater than 0.1.mp4

00:46

4. Pandas - Greater than 0.1 - Code.html

5. Pandas - Selecting with given Columns and Rows.mp4

01:26

6. Pandas - Selecting with given Columns and Rows - Code.html

7. Pandas - Selecting Data with Loc & Slicing.mp4

01:54

8. Pandas - Selecting Data with Loc & Slicing - Code.html

9. Pandas - Many ways of Retrieving Column.mp4

01:16

10. Pandas - Many ways of Retrieving Column - Code.html

11. Pandas - Select Data related to Singapore.mp4

01:23

12. Pandas - Select Data related to Singapore - Code.html

13. Pandas - Select years after 2019.mp4

00:57

14. Pandas - Select years after 2019 - Code.html

15. Pandas - Generosity between two values.mp4

01:28

16. Pandas - Generosity between two values - Code.html

17. Pandas - Life expectancy below 40.mp4

00:49

18. Pandas - Life expectancy below 40 - Code.html

19. Pandas - Using columns to set condition.mp4

00:53

20. Pandas - Using columns to set condition - Code.html

21. Pandas - Zimbabwe & Singapore.mp4

01:32

22. Pandas - Zimbabwe & Singapore - Code.html

65. Pandas - Data Cleaning

1. Introduction.mp4

01:34

2. Pandas - Checking for NaN.mp4

03:47

3. Pandas - Checking for NaN - Code.html

4. Pandas - Removing NaN.mp4

02:48

5. Pandas - Removing NaN - Code.html

6. Pandas - Removing NaN II.mp4

02:30

7. Pandas - Replacing NaN with a value.mp4

04:56

8. Pandas - Replacing NaN with a value - Code.html

9. Pandas - Replacing NaN in one Column.mp4

02:16

10. Pandas - Replacing NaN in one Column - Code.html

11. Pandas - Replacing NaN with mean, mode & median.mp4

01:52

12. Pandas - Data Cleaning - Sales.mp4

05:17

13. Pandas - Data Cleaning - Sales -Code.html

66. Pandas - GroupBy

1. Pandas - GroupBy Intro.mp4

01:32

2. Pandas - GroupBy Intro - Code.html

3. Pandas - GroupBy Challenge & Solution.mp4

02:32

4. Pandas - GroupBy Challenge & Solution - Code.html

67. Pandas with SQL

1. Installation, Connection & Import.mp4

07:54

2. Installation, Connection & Import - Code.html

3. Importing Fewer Columns From SQL to Pandas.mp4

02:27

4. Importing Fewer Columns From SQL to Pandas - Code.html

5. Querying SQL Database from Pandas.mp4

02:22

6. Querying SQL Database from Pandas - Code.html

7. Creating Table in SQL from Pandas.mp4

03:47

8. Creating Table in SQL from Pandas - Code.html

9. read sql() method - A two in one Method.mp4

02:47

10. read sql() method - A two in one Method - Code.html

68. Pandas with Excel

1. Pandas - Importing Excel File.mp4

01:00

2. Pandas - Importing Excel File - Code.html

3. Pandas - Cleaning Excel Data Set While Importing.mp4

05:28

4. Pandas - Cleaning Excel Data Set While Importing - Code.html

5. Pandas - Saving an Excel File.mp4

01:20

6. Pandas - Saving an Excel File - Code.html

7. Pandas Save Excel File Without Index.mp4

00:48

8. Pandas Save Excel File Without Index - Code.html

9. Pandas - Shifting an Excel Sheet.mp4

01:29

10. Pandas - Shifting an Excel Sheet - Code.html

69. Matplotlib - Introduction

1. Matplotlib - What is Matplotlib.mp4

01:44

2. Matplotlib - Installation.mp4

01:25

70. Matplotlib - Plot

1. Matplotlib - Understaning Plot.mp4

03:11

2. Matplotlib - Understaning Plot.html

3. Matplotlib - dot, x, square.mp4

01:45

4. Matplotlib - dot, x, square - Code.html

5. Matplotlib - Plotting Multiple Points.mp4

01:24

6. Matplotlib - Plotting Multiple Points - Code.html

7. Matplotlib - Plotting Without x-axis.mp4

01:30

8. Matplotlib - Plotting Without x-axis - Code.html

71. Matplotlib - Markers

1. Matplotlib - Understanding Markers.mp4

01:50

2. Matplotlib - Format String.mp4

02:56

3. Matplotlib - Marker Size.mp4

01:32

4. Matplotlib - Marker Colour.mp4

01:48

5. Matplotlib - Range of Marker Colours.mp4

01:40

72. Matplotlib - Line

1. Matplotlib - Line Style.mp4

01:58

2. Matplotlib - Line Colours.mp4

02:24

3. Matplotlib - Line Width.mp4

00:47

4. Matplotlib - Multiple Lines.mp4

01:21

5. Matplotlib - Multiple Lines More.mp4

02:27

73. Matplotlib - Figure

1. Matplotlib - Understanding Figure.mp4

07:17

74. Matplotlib - Label & Title

1. Matplotlib - Loc.mp4

01:00

2. Matplotlib - Label.mp4

01:09

3. Matplotlib - Title.mp4

00:31

4. Matplotlib - Font Properties.mp4

02:21

75. Matplotlib - Legend

1. Matplotlib - Understanding Legend.mp4

02:16

2. Matplotlib - Understanding Legend - More.mp4

01:09

3. Matplotlib - Legend Repositioning.mp4

00:38

4. Matplotlib - Legend Outside.mp4

01:56

76. Matplotlib - Grid

1. Matplotlib - Understanding Grid.mp4

00:50

2. Matplotlib - Grid Properties.mp4

00:40

77. Matplotlib - SubPlot

1. Matplotlib - Understanding Subplot.mp4

02:13

2. Matplotlib - Understanding Subplot - More.mp4

02:10

3. Matplotlib - Subplot title and Super title.mp4

01:24

78. Matplotlib - Scatter Plot

1. Matplotlib - Understanding Scatter Plot.mp4

01:32

2. Matplotlib - Scatter Plot - Colour Dots.mp4

01:32

3. Matplotlib - Scatter Plot - Size of Dots.mp4

01:32

4. Matplotlib - Scatter Plot - Size of Dots - Code.html

5. Matplotlib - Scatter Plot - Colour Map.mp4

05:35

6. Matplotlib - Scatter Plot - Colour Map - Code.html

7. Matplotlib - Scatter Plot - Alpha.mp4

01:50

8. Matplotlib - Scatter Plot - Groups.mp4

01:29

9. Matplotlib - Scatter Plot - Groups - Code.html

10. Matplotlib - Scatter Plot - 20 Random Circles.mp4

05:54

79. Matplotlib - Pie

1. Matplotlib - Introduction to Pie Chart.mp4

01:14

2. Matplotlib - Pie - Label.mp4

00:55

3. Matplotlib - Pie - Legend.mp4

00:52

4. Matplotlib - Pie - Legend Title.mp4

00:39

5. Matplotlib - Pie - Explode.mp4

02:01

6. Matplotlib - Shadow for Widget.mp4

00:44

7. Matplotlib - Pie - Colour.mp4

00:49

80. Matplotlib - Bar

1. Matplotlib - Understanding Bar Chart.mp4

02:41

2. Matplotlib - Bar - Increasing & Reducing Font Size.mp4

01:25

3. Matplotlib - Bar - Increasing & Reducing Font Size - Code.html

4. Matplotlib - Bar - Changing Specific Bar Colour.mp4

01:18

5. Matplotlib - Bar - Changing Specific Bar Colour - Code.html

81. Matplotlib - 3D

1. Matplotlib - 3D - Introduction.mp4

02:02

2. Matplotlib - 3D - Introduction - Code.html

3. Matplotlib - 3D with Scatter Plot.mp4

04:48

4. Matplotlib - 3D with Scatter Plot - Code.html

82. Matplotlib - Trigonometric Plotting

1. Understanding Trigonometric (Sin, Cos & Tan) Plotting.mp4

02:34

2. Understanding Trigonometric (Sin, Cos & Tan) Plotting - Code.html

83. Matplotlib - Challenges & Solutions - Lines

1. Challenge & Solution - 1.mp4

01:11

2. Challenge & Solution - 1 - Code.html

3. Challenge & Solution - 2.mp4

01:48

4. Challenge & Solution - 2 - Code.html

5. Challenge & Solution - 3.mp4

02:40

6. Challenge & Solution - 3 - Code.html

7. Challenge & Solution - 4.mp4

01:21

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9. Challenge & Solution - 5.mp4

04:59

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11. Challenge & Solution - 6.mp4

02:22

12. Challenge & Solution - 6- Code.html

84. Matplotlib - Challenge & Solution - Figure

1. Challenge & Solution.mp4

02:35

2. Challenge & Solution - Code.html

85. Matplotlib - Challenge & Solution - Subplot

1. Challenge & Solution.mp4

02:31

2. Challenge & Solution - Code.html

86. Matplotlib - Challenges & Solutions - Bar Chart

1. Challenge & Solution - 1.mp4

03:54

2. Challenge & Solution - 1 - Code.html

3. Challenge & Solution - 2.mp4

01:52

4. Challenge & Solution - 2 - Code.html

5. Challenge & Solution - 3.mp4

05:39

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7. Challenge & Solution - 4.mp4

02:31

8. Challenge & Solution - 4 - Code.html

87. Matplotlib - Challenges & Solution - Pie Chart

1. Challenge & Solution - 1.mp4

05:36

2. Challenge & Solution - 1 - Code.html

3. Challenge & Solution - 2.mp4

04:44

4. Challenge & Solution - 2 - Code.html

5. Challenge & Solution - 3.mp4

05:19

6. Challenge & Solution - 3 - Code.html

88. Matplotlib - Challenge & Solution - 3D

1. Challenge & Solution.mp4

07:36

2. Challenge & Solution - Code.html

89. Matplotlib - More Challenges & Solutions

1. Challenge & Solution - 1.mp4

06:05

2. Challenge & Solution - 1 - Code.html

3. Challenge & Solution - 2.mp4

05:04

4. Challenge & Solution - 2 - Code.html

90. Recommended Course

1. Mathematics, Probability & Statistics for Machine Learning.html

91. Bonus Section

1. Please check out my other courses.html

Description

Python NumPy, Pandas, and Matplotlib for Data Analysis, Data Science and Machine Learning. Pre-machine learning Analysis

What You'll Learn?

Go from absolute beginner to become a confident Python NumPy, Pandas and Matplotlib user
Dare to get the most out of Python NumPy, Pandas and Matplotlib
Go deeper to understand complex topics in Python NumPy, Pandas and data visualisation
Learn Python NumPy, Pandas and Matplotlib through several exercises and solutions
Acquire the required Python NumPy, Pandas and Matplotlib knowledge you need to excel in Data Science, Machine Learning, Ai and Deep Learning
Be trained by expert

Who is this for?

All levels of students

What You Need to Know?

Just a little knowledge of Python

More details

Description
Welcome to NumPy, Pandas and Matplotlib A-Zâ„¢: for Machine Learning
NumPy is a leading scientific computing library in Python while Pandas is for data manipulation and analysis. Also, learn to use Matplotlib for data visualization. Whether you are trying to go into Data Science, dive into machine learning, or deep learning, NumPy and Pandas are the top Modules in Python you should understand to make the journey smooth for you. In this course, we are going to start from the basics of Python NumPy and Pandas to the advanced NumPy and Pandas. This course will give you a solid understanding of NumPy, Pandas, and their functions.
At the end of the course, you should be able to write complex arrays for real-life projects, manipulate and analyze real-world data using Pandas.

WHOÂ ISÂ THISÂ COURSEÂ FOR?Â

âˆš This course is for you if you want to learn NumPy, Pandas, and Matplotlib for the first time or get a deeper knowledge of NumPy and Pandas to increase your productivity with deep and Machine learning.
âˆš This course is for you if you are coming from other programming languages and want to learn Python NumPy and Pandas fast and know it really well.
âˆš This course is for you if you are tired of NumPy,Â Pandas, and Matplotlib courses that are too brief, too simple, or too complicated.
âˆš This course is for you if you want to build real-world applications using NumPy or Panda and visualize them with Matplotlib.
âˆš This course is for you if you have to get the prerequisite knowledge to understanding Data Science and Machine Learning using NumPy and Pandas.
âˆš This course is for you if you want to master the in-and-out of NumPy, Pandas, and data visualization.
âˆš This course is for you if you want to learn NumPy and Pandas by doing exciting real-life challenges that will distinguish you from the crowd.
âˆš This course is for you if plan to pass an interview soon.

Who this course is for:
All levels of students

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Donatus holds a first degree in Electrical Engineering with first class, MSc in Computer Science, Ph.D. in Management, and more than fifteen (15) industrial certificates. For over two decades, Don has worked as Process Engineer, Network Architect, Project Manager, and Data Scientist in Banking, Oil & Gas, and IT industries.With several years of experience in teaching, Donatus has empowered many IT professionals in the area of Network Engineering, Programming, Data Science, and Machine learning both offline and online. He provides training on data science and related courses to individual and corporate clients. Many students who graduated from his classes end up gaining full-time employment. He had also taught in India, Singapore, and Malaysia. He understands what makes students enjoy lectures and what makes them assimilate with ease.His recent focus is to bring you the best training in Database, Data Science, Machine Learning, and related courses.Do you have an interest in learning with a lot of practice?Join him right away!Industrial Certificates:1 - Project Management Professional (PMP) – Above Target2 - Neo4j Certified Professional3 - Check Point Certified Security Expert (CCSE)4 - Check Point Certified Security Administrator (CCSA)5 - Cisco Certified Network Professional (CCNP)6 - Cisco Certified Network Associate (CCNA)7 - Cisco Certified Design Professional (CCDP)8 - Cisco Certified Design Associate (CCDA)9 - Cisco Certified Network Professional Voice (CCNPv)10 - Cisco Certified Network Associate Voice (CCNAv)11 - Cisco Advanced Wireless Field Specialist12 - Certified Wireless Security Professional (CWSP)13 - Certified Wireless Network Administrator (CWNA)14 - Juniper Networks Certified Internet Specialist (JNCIS) 15 - CompTia Security+ Certified Professional16 - NEBOSH International General Certificate (NEBOSH)17 - BS OHSAS Internal Auditor Certificate (OHSAS 18001:2007)18 - IOSH Managing Safely (IOSH)19 - IOSH Working Safely (IOSH)

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