Udemy - The Complete Self-Driving Car Course

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size8.3 GB
  • Uploaded Bydomhen
  • Downloads114
  • Last checkedSep. 24th '18
  • Date uploadedSep. 23rd '18
  • Seeders 5
  • Leechers8
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Infohash : 56C7967901581787872C3631A7FD33AB89571633

What Will I Learn?
Learn to apply Computer Vision and Deep Learning techniques to build automotive-related algorithms
Understand, build and train Convolutional Neural Networks with Keras
Simulate a fully functional Self-Driving Car with Convolutional Neural Networks and Computer Vision
Train a Deep Learning Model that can identify between 43 different Traffic Signs
Learn to use essential Computer Vision techniques to identify lane lines on a road
Learn to build and train powerful Neural Networks with Keras
Understand Neural Networks at the most fundamental perceptron-based level

Requirements
A working computer
No experience required!

Description
Self-driving cars, have rapidly become one of the most transformative technologies to emerge. Fuelled by Deep Learning algorithms, they are continuously driving our society forward, and creating new opportunities in the mobility sector.

Deep Learning jobs command some of the highest salaries in the development world. This is the first, and only course which makes practical use of Deep Learning, and applies it to building a self-driving car, one of the most disruptive technologies in the world today.

Learn & Master Deep Leaning in this fun and exciting course with top instructor Rayan Slim. With over 28000 students, Rayan is a highly rated and experienced instructor who has followed a “learn by doing” style to create this amazing course.

You’ll go from beginner to Deep Learning expert and your instructor will complete each task with you step by step on screen.

By the end of the course, you will have built a fully functional self-driving car fuelled entirely by Deep Learning. This powerful simulation will impress even the most senior developers and ensure you have hands on skills in neural networks that you can bring to any project or company.

This course will show you how to:

Use Computer Vision techniques via OpenCV to identify lane lines for a self-driving car.

Learn to train a Perceptron-based Neural Network to classify between binary classes.

Learn to train Convolutional Neural Networks to identify between various traffic signs.

Train Deep Neural Networks to fit complex datasets.

Master Keras, a power Neural Network library written in Python.

Build and train a fully functional self driving car to drive on its own!

No experience required. This course is designed to take students with no programming/mathematics experience to accomplished Deep Learning developers.

This course also comes with all the source code and friendly support in the Q&A area.

Files:

The Complete Self-Driving Car Course - Applied Deep Learning 12. Traffic Sign Classification
  • 3. Preprocessing Images.mp4 (330.4 MB)
  • 1. Overview.mp4 (14.5 MB)
  • 1. Overview.vtt (1.3 KB)
  • 2. Traffic Signs Starter Code.html (1.5 KB)
  • 3. Preprocessing Images.vtt (43.1 KB)
  • 3.1 Traffic Signs Starter Project.ipynb.zip.zip (1.5 KB)
  • 4. leNet Implementation.mp4 (129.4 MB)
  • 4. leNet Implementation.vtt (20.3 KB)
  • 5. Fine-tuning Model.mp4 (117.0 MB)
  • 5. Fine-tuning Model.vtt (15.3 KB)
  • 6. Resources Needed for Testing.html (2.1 KB)
  • 7. Testing.mp4 (63.1 MB)
  • 7. Testing.vtt (0.3 KB)
  • 8. Fit Generator.mp4 (159.8 MB)
  • 8. Fit Generator.vtt (0.3 KB)
  • 9. Final Source Code.html (7.3 KB)
  • 10. Section 12 - Outro.mp4 (9.9 MB)
  • 10. Section 12 - Outro.vtt (0.3 KB)
1. Introduction
  • 1. Introduction.vtt (3.2 KB)
  • 1. Introduction.mp4 (40.4 MB)
2. Installation
  • 1. Overview.mp4 (10.5 MB)
  • 1. Overview.vtt (1.0 KB)
  • 2. Anaconda Distribution.mp4 (26.3 MB)
  • 2. Anaconda Distribution.vtt (2.9 KB)
  • 3. Jupyter Notebooks.mp4 (41.9 MB)
  • 3. Jupyter Notebooks.vtt (6.1 KB)
  • 4. Text Editor.mp4 (29.1 MB)
  • 4. Text Editor.vtt (3.2 KB)
  • 5. Outro.mp4 (5.5 MB)
  • 5. Outro.vtt (0.7 KB)
3. Python Crash Course (Optional)
  • 1. Python Crash Course Part 1 - Data Types.mp4 (15.2 MB)
  • 1. Python Crash Course Part 1 - Data Types.vtt (1.3 KB)
  • 2. Arithmetic Operations.mp4 (25.4 MB)
  • 2. Arithmetic Operations.vtt (4.8 KB)
  • 3. Variables.mp4 (27.7 MB)
  • 3. Variables.vtt (5.5 KB)
  • 4. Numeric Data Types.mp4 (23.5 MB)
  • 4. Numeric Data Types.vtt (4.1 KB)
  • 5. String Data Types.mp4 (42.0 MB)
  • 5. String Data Types.vtt (5.7 KB)
  • 6. Booleans.mp4 (24.2 MB)
  • 6. Booleans.vtt (4.6 KB)
  • 7. Methods.mp4 (20.7 MB)
  • 7. Methods.vtt (3.3 KB)
  • 8. Lists.mp4 (35.8 MB)
  • 8. Lists.vtt (5.7 KB)
  • 9. Slicing.mp4 (55.6 MB)
  • 9. Slicing.vtt (7.8 KB)
  • 10. Membership Operators.mp4 (13.8 MB)
  • 10. Membership Operators.vtt (2.6 KB)
  • 11. Mutability.mp4 (33.0 MB)
  • 11. Mutability.vtt (4.1 KB)
  • 12. Mutability II.mp4 (31.6 MB)
  • 12. Mutability II.vtt (3.6 KB)
  • 13. Common Functions & Methods.mp4 (46.8 MB)
  • 13. Common Functions & Methods.vtt (7.1 KB)
  • 14. Tuples.mp4 (23.1 MB)
  • 14. Tuples.vtt (3.3 KB)
  • 15. Sets.mp4 (19.6 MB)
  • 15. Sets.vtt (2.7 KB)
  • 16. Dictionaries.mp4 (35.3 MB)
  • 16. Dictionaries.vtt (4.8 KB)
  • 17. Compound Data Structures.mp4 (20.2 MB)
  • 17. Compound Data Structures.vtt (2.4 KB)
  • 18. Part 1 - Outro.mp4 (3.6 MB)
  • 18. Part 1 - Outro.vtt (0.4 KB)
  • 19. Part 2 - Control Flow.mp4 (11.5 MB)
  • 19. Part 2 - Control Flow.vtt (1.0 KB)
  • 20. If, else.mp4 (27.2 MB)
  • 20. If, else.vtt (4.4 KB)
  • 21. elif.mp4 (49.0 MB)
  • 21. elif.vtt (6.5 KB)
  • 22. Complex Comparisons.mp4 (29.5 MB)
  • 22. Complex Comparisons.vtt (4.7 KB)
  • 23. For Loops.mp4 (38.5 MB)
  • 23. For Loops.vtt (6.6 KB)
  • 24. For Loops II.mp4 (15.1 MB)
  • 24. For Loops II.vtt (2.9 KB)
  • 25. While Loops.mp4 (20.2 MB)
  • 25. While Loops.vtt (3.1 KB)
  • 26. Break.mp4 (19.7 MB)
  • 26. Break.vtt (3.5 KB)
  • 27. Part 2 - Outro.mp4 (4.5 MB)
  • 27. Part 2 - Outro.vtt (0.4 KB)
  • 28. Part 3 - Functions.mp4 (11.4 MB)
  • 28. Part 3 - Functions.vtt (1.1 KB)
  • 29. Functions.mp4 (31.6 MB)
  • 29. Functions.vtt (5.3 KB)
  • 30. Scope.mp4 (13.2 MB)
  • 30. Scope.vtt (1.8 KB)
  • 31. Doc Strings.mp4 (19.6 MB)
  • 31. Doc Strings.vtt (2.6 KB)
  • 32. Lambda & Higher Order Functions.mp4 (28.4 MB)
  • 32. Lambda & Higher Order Functions.vtt (6.5 KB)
  • 33. Part 3 - Outro.mp4 (8.8 MB)
  • 33. Part 3 - Outro.vtt (0.8 KB)
4. NumPy Crash Course (Optional)
  • 1. Overview.mp4 (10.6 MB)
  • 1. Overview.vtt (0.9 KB)
  • 2. Vector Addition - Arrays vs Lists.mp4 (86.8 MB)
  • 2. Vector Addition - Arrays vs Lists.vtt (12.7 KB)
  • 3. Multidimensional Arrays.mp4 (96.8 MB)
  • 3. Multidimensional Arrays.vtt (11.8 KB)
  • 4. One Dimensional Slicing.mp4 (27.8 MB)
  • 4. One Dimensional Slicing.vtt (3.9 KB)
  • 5. Reshaping.mp4 (23.4 MB)
  • 5. Reshaping.vtt (3.5 KB)
  • 6. Multidimensional Slicing.mp4 (49.2 MB)
  • 6. Multidimensional Slicing.vtt (7.3 KB)
  • 7. Manipulating Array Shapes.mp4 (47.8 MB)
  • 7. Manipulating Array Shapes.vtt (8.4 KB)
  • 8. Matrix Multiplication.mp4 (34.3 MB)
  • 8. Matrix Multiplication.vtt (4.2 KB)
  • 9. Stacking.mp4 (82.3 MB)
  • 9. Stacking.vtt (12.9 KB)
  • 10. Part 4 - Outro.mp4 (2.5 MB)
  • 10. Part 4 - Outro.vtt (0.2 KB)
5. Computer Vision Finding Lane-Lines
  • 1. Overview.mp4 (9.0 MB)
  • 1. Overview.vtt (0.8 KB)
  • 2. Image needed for the next lesson.html (0.1 KB)
  • 2.1 Image.zip.zip (759.1 KB)
  • 3. Loading Images.mp4 (30.7 MB)
  • 3. Loading Images.vtt (4.8 KB)
  • 3.1 Im

Code:

  • UDP://TRACKER.LEECHERS-PARADISE.ORG:6969/ANNOUNCE