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The Complete Data Science and Image Recognition Course with Python
Python Language Basics
00. Introduction (4:47)
01. Intro To Python (5:46)
02. Variables (19:34)
03. Type Conversion Examples (10:21)
04. Operators (7:21)
05. Operators Examples (22:09)
06. Collections (8:39)
07. Lists (11:55)
08. Multidimensional List Examples (8:22)
09. Tuples Examples (8:51)
10. Dictionaries Examples (14:41)
11. Ranges Examples (8:46)
12. Conditionals (6:58)
13. If Statement Examples (10:32)
14. If Statement Variants Examples (11:35)
15. Loops (7:17)
16. While Loops Examples (11:47)
17. For Loops Examples (11:35)
18. Functions (8:04)
19. Functions Examples (9:33)
20. Parameters And Return Values Examples (14:08)
21. Classes and Objects (11:30)
22. Classes Example (13:28)
23. Objects Examples (10:10)
24. Inheritance Examples (17:43)
25. Static Members Example (11:20)
26. Summary and Outro (4:23)
Intro to Python Slides
Python_Language_Basics Code
Numpy 2020
00. Course Intro (5:11)
01. Intro to Numpy (6:20)
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)
Numpy_Code
Numpy Slides
Pandas 2020
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 (19:20)
06. Getting Properties of Series (13:04)
07. Modifying Series (19:01)
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)
pandasPracticeCSV
Pandas_Code
Pandas Slides
PyPlot 2020
00. Course Intro (5:30)
01. Intro to Pyplot (5:10)
02. Installing Matplotlib (5:51)
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)
Pyplot Code
Machine Learning Theory 2020
00. Course Intro (6:04)
01. Quick Intro to Machine Learning (9:00)
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)
Intro to Machine Learning Slides
Intro to Tensorflow 2020
00. Course Intro (6:10)
01. Intro to Tensorflow (5:32)
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 (12:42)
08. Linear Regression Model - Testing the Model (5:22)
09. Summary and Outro (2:55)
Intro to Tensorflow Slides
Linear_Regression Code
Image Recognition with MNIST
00. Course Intro (6:57)
01. Intro to Image Recognition (14:07)
02. Intro to MNIST (4:42)
03. Building a CNN Part 1 - Obtaining Data (15:40)
04. Building a CNN Part 2 - Building the Model (10:14)
05. Building a CNN Part 3 - Adding Loss and Optimizer Functions (4:57)
06. Building a CNN Part 4 - Train and Test Functions (10:58)
07. Building a CNN Part 5 - Train and Test the Model (9:17)
08. MNIST Image Recognition with Keras Sequential Model (13:23)
09. Summary and Outro (2:55)
Image_Recognition_with_MNIST Code
Image_Recognition_with_MNIST_and_Keras Code
Image Recognition with MNIST Slides
06. Building a CNN Part 4 - Train and Test Functions
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