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Python Data Science Fundamentals - Comprehensive Bundle
Numpy
Source Files
00. Course Intro (5:11)
01. Intro To Numpy (6:21)
02. Installing Numpy (3:59)
03. Creating Numpy Arrays (16:55)
04. Creating Numpy Matrices (11:57)
05. Getting And Setting Numpy Elements (16:59)
06. Arithmetic Operations On Numpy Arrays (11:56)
07. Numpy Functions Part 1 (19:13)
08. Numpy Functions Part 2 (12:36)
09. Summary And Outro (3:01)
Complete Beginners Data Analysis with Pandas and Python
Source Files
00. Panda Course Introduction (5:43)
01. Intro To Pandas (7:55)
02. Installing Pandas (5:28)
03. Creating Pandas Series (20:34)
04. Date Ranges (11:29)
05. Getting Elements From Series (19:21)
06. Getting Properties Of Series (13:04)
07. Modifying Series (19:02)
08. Operations On Series (11:48)
09. Creating Pandas Dataframes (22:57)
10. Getting Elements From Dataframes (25:12)
11. Getting Properties From Dataframes (17:44)
12. Dataframe Modification (36:24)
13. Dataframe Operations (20:09)
14. Dataframe Comparisons And Iteration (15:35)
15. Reading Csvs (12:00)
16.Summary And Outro (4:14)
Pyplot
Pyplot Code
00. Course Intro (5:30)
01. Intro To Pyplot (5:11)
02. Installing Matplotlib (5:52)
03. Basic Line Plot (7:53)
04. Customizing Graphs (10:47)
05. Plotting Multiple Datasets (8:10)
06. Bar Chart (6:26)
07. Pie Chart (9:13)
08. Histogram (10:14)
09. 3D Plotting (6:28)
10. Course Outro (4:09)
TensorFlow
Intro to Tensorflow - Source Files
00. Course Intro (6:10)
01. Intro To Tensorflow (5:33)
02. Installing Tensorflow (3:52)
03. Intro To Linear Regression (9:26)
04. Linear Regression Model - Creating Dataset (5:49)
05. Linear Regression Model - Building The Model (7:22)
06. Linear Regression Model - Creating A Loss Function (5:57)
07. Linear Regression Model - Training The Model (12:43)
08. Linear Regression Model - Testing The Model (5:22)
09. Summary And Outro (2:55)
Machine Learning theory
Intro to Machine Learning Slides
00. Course Intro (6:05)
01. Quick Intro To Machine Learning (9:01)
02. Deep Dive Into Machine Learning (6:01)
03. Problems Solved With Machine Learning Part 1 (13:26)
04. Problems Solved With Machine Learning Part 2 (16:25)
05. Types Of Machine Learning (10:15)
06. How Machine Learning Works (11:40)
07. Common Machine Learning Structures (13:51)
08. Steps To Build A Machine Learning Program (16:34)
09. Summary And Outro (2:49)
Review Sentiment analysis
Source Files
00. Course Intro (6:19)
01. How Machines Interpret Text (15:23)
02. Building The Model Part 1 - Examining Dataset (12:27)
03. Building The Model Part 2 - Formatting Dataset (15:14)
04. Building The Model Part 3 - Building The Model (10:30)
05. Building The Model Part 4 - Training The Model (5:42)
06. Building The Model Part 5 - Testing The Model (9:26)
07. Course Summary And Outro (3:29)
01. Quick Intro To Machine Learning
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