Machine Learning For Absolute Beginners 3 Levels

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9:09:03

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Level 1

01-Welcome!.mp4

06:38

02-Artificial Intelligence (AI) - The Future.mp4

04:22

03-Artificial Intelligence (AI).mp4

06:14

04-Classical Programming.mp4

03:13

05-Machine Learning (ML).mp4

07:13

06-Deep Learning.mp4

07:51

07-Applied versus Generalized Artificial Intelligence (AI).mp4

04:19

08-Why Do We Need AI Today.mp4

09:21

09-Machine Learning (ML) Terminology.mp4

01:20

10-The Black Box Metaphor.mp4

03:04

11-Features and Labels.mp4

05:09

12-Training a Model.mp4

04:49

13-Aiming for Generalization.mp4

11:23

14-The Degree of Supervision.mp4

01:45

15-Supervised Learning.mp4

06:16

16-Classification.mp4

05:23

17-Regression.mp4

07:13

18-Unsupervised Learning.mp4

03:40

19-Clustering.mp4

05:09

20-Dimension Reduction.mp4

05:48

21-Reinforcement Learning.mp4

05:57

22-Decision-making Agent.mp4

07:04

23-Lets Recap and Thank You!.mp4

06:40

Level 2

01-Welcome.mp4

02:19

02-Anaconda Installation.mp4

04:22

03-Jupyter Lab Overview.mp4

03:51

04-Working with a Jupyter Notebook.mp4

14:16

05-Overview.mp4

02:52

06-Variables and Data Types.mp4

07:22

07-Strings.mp4

07:44

08-Lists.mp4

09:44

09-The if and for Loop Statements.mp4

07:08

10-Functions.mp4

07:59

11-Dictionaries.mp4

11:01

12-Classes, Objects, Attributes, and Methods.mp4

07:28

13-Importing Modules.mp4

07:34

14-Libraries for Data Science Projects.mp4

07:03

15-Exercise 1- Python Fundamentals.mp4

00:33

16-Overview.mp4

02:59

17-Series Data Structure (1D).mp4

12:41

18-DataFrame Data Structure (2D).mp4

04:52

19-Data Selection in a Dataframe.mp4

14:55

20-Exercise 2 pandas Series and Dataframe.mp4

00:34

21-Overview.mp4

01:14

22-Kaggle and the Titanic Dataset.mp4

05:48

23-Loading Tabular Data File.mp4

06:35

24-Adjusting the Loading Parameters.mp4

13:06

25-Previewing the DataFrame.mp4

08:14

26-Using Summary Statistics.mp4

04:48

27-The Concept of Methods Chaining.mp4

05:17

28-Sorting and Ranking.mp4

03:13

29-Filtering.mp4

04:53

30-Grouping.mp4

04:52

31-Exercise 3 - Data Loading and Analysis.mp4

00:34

32-Overview.mp4

02:07

33-Removing Columns or Rows.mp4

04:17

34-Removing Duplicate Rows.mp4

08:37

35-Renaming Column Labels.mp4

03:32

36-Dropping Missing Values.mp4

07:29

37-Filling-in Missing Values.mp4

03:32

38-Creating Dummy Variables.mp4

08:16

39-Exporting Data into Files.mp4

02:39

40-Exercise 4 - Data Cleaning and Transformation.mp4

00:27

41-Recap and Thank You.mp4

02:45

Level 3

01-Welcome.mp4

03:22

02-Our Overall Learning Path.mp4

02:13

03-How to Practice.mp4

02:31

04-Data Visualization - Overview.mp4

02:11

05-Matplotlib - Overview.mp4

08:23

06-Matplotlib - Figures and Axes.mp4

03:23

07-Matplotlib - The Object-Oriented (OO) and Pyplot Interfaces.mp4

06:59

08-Matplotlib - APIs Reference Review.mp4

05:37

09-Seaborn - Overview.mp4

03:50

10-Seaborn - Figure-level and Axes-level Functions.mp4

06:21

11-Seaborn - Chart Customization.mp4

04:44

12-Seaborn - The API Reference Review.mp4

04:00

13-A Little Bit about NumPy.mp4

06:40

14-The Right Chart for the Right Job.mp4

02:50

15-Ranking and Proportion Charts - An Overview.mp4

01:20

16-Bar Chart.mp4

10:20

17-Grouped Bar Chart.mp4

09:07

18-Lollipop Chart.mp4

04:04

19-Stacked Bar Chart.mp4

03:34

20-Pie Chart.mp4

03:51

21-Treemap.mp4

06:25

22-Optimizing Colors.mp4

06:32

23-Trend and Distribution Charts - Overview.mp4

01:56

24-Line Chart.mp4

06:59

25-Area Chart.mp4

01:58

26-Stacked Area Chart.mp4

03:43

27-Histogram Chart.mp4

06:43

28-Density Curve Chart.mp4

05:38

29-Box-and-Whisker Chart.mp4

09:30

30-Bee-swarm Chart.mp4

02:30

31-Correlation Charts - Overview.mp4

02:41

32-Scatter Chart.mp4

10:26

33-Correlogram.mp4

03:29

34-Heat Map.mp4

08:34

35-Hexbin Map.mp4

04:21

36-Lets Recap and Thank You.mp4

02:55

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Machine Learning

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Packt is a publishing company founded in 2003 headquartered in Birmingham, UK, with offices in Mumbai, India. Packt primarily publishes print and electronic books and videos relating to information technology, including programming, web design, data analysis and hardware.