Python Ping Pong Game Part 7 - Displaying/Keeping Score

Let's learn Python By Creating a Ping Pong Game

Check out the full course:

Featuring:
1.Python Strings and RNG
2. Conditional Statements
3. Lists and Bundle Storage
4. Finite State Machines with Python
5. Loops
6. Functions
7. Dictionaries
8. Exceptions and Crash Handling
9. Python Built-In Functions
10. Object Oriented Programming
11. Decorators
12. Handling text Files
13. Handling Compressed Files
14. Data Plotting with Matplotlib
15. Directory Management.
16. Command Line Based Applications
17. Numpy and Math
18. Image Processing With OpenCV
19. Video Processing
20. Object Tracking
21. Pandas And Tabular Data
22. GUI Based Apps
23. Converting Python to Stand-Alone Software
24. Recommender Systems with Netflix
25. OCR and Image to Text Conversion
26. Data Analysis Breakdown
27. Artificial Data Generation
28. Machine Learning Breakdown
29. Features Engineering
30. Seaborn for Data Visualization
31. Gaussian Naive Bayes
32. Principal Component Analysis (PCA)
33. Linear Regression
34. Polynomial Regression
35. K-means Clustering
36. Support Vector Machine (SVM)
37. Linear Discriminate Analysis (LDA)
38. t-SNE
39. Hierarchical Clustering
40. Time Series Analysis
41. Decision Trees
42. Random Forests
43. Reinforcement Learning
44. Natural Language Processing (NLP)
45. Building A Messages and Emails Spam Filter
46. Market Segmentation
47. Analyzing House Pricing
48. Deep learning Breakdown
49. Artificial Neural Networks
50. Image Classification
51. Convolutional Neural Networks
52. Automating Accountant Job
53. Building Web AppsFeaturing:
1.Python Strings and RNG
2. Conditional Statements
3. Lists and Bundle Storage
4. Finite State Machines with Python
5. Loops
6. Functions
7. Dictionaries
8. Exceptions and Crash Handling
9. Python Built-In Functions
10. Object Oriented Programming
11. Decorators
12. Handling text Files
13. Handling Compressed Files
14. Data Plotting with Matplotlib
15. Directory Management.
16. Command Line Based Applications
17. Numpy and Math
18. Image Processing With OpenCV
19. Video Processing
20. Object Tracking
21. Pandas And Tabular Data
22. GUI Based Apps
23. Converting Python to Stand-Alone Software
24. Recommender Systems with Netflix
25. OCR and Image to Text Conversion
26. Data Analysis Breakdown
27. Artificial Data Generation
28. Machine Learning Breakdown
29. Features Engineering
30. Seaborn for Data Visualization
31. Gaussian Naive Bayes
32. Principal Component Analysis (PCA)
33. Linear Regression
34. Polynomial Regression
35. K-means Clustering
36. Support Vector Machine (SVM)
37. Linear Discriminate Analysis (LDA)
38. t-SNE
39. Hierarchical Clustering
40. Time Series Analysis
41. Decision Trees
42. Random Forests
43. Reinforcement Learning
44. Natural Language Processing (NLP)
45. Building A Messages and Emails Spam FIlter
46. Market Segmentation
47. Analyzing House Pricing
48. Deep learning Breakdown
49. Artificial Neural Networks
50. Image Classification
51. Convultional Neural Networks
52. Automating Accountant Job
53. Building Web Apps