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Udemy | Algorithmic Problems in Python [FTU] TGx Exclusive

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Category:

Other > Training

Language:

English

Total Size:

907.00 MB

Info Hash:

8c0be3a454c0c48a94e7809bc6dfc9754fe9d82a

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Prom3th3uS :_verified_uploader:

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21-07-2019 03:33

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571

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File	Size
0. Websites you may like/1. (FreeTutorials.Us) Download Udemy Paid Courses For Free.url	328.00 B
0. Websites you may like/2. (FreeCoursesOnline.Me) Download Udacity, Masterclass, Lynda, PHLearn, Pluralsight Free.url	286.00 B
0. Websites you may like/3. (NulledPremium.com) Download Cracked Website Themes, Plugins, Scripts And Stock Images.url	163.00 B
0. Websites you may like/4. (FTUApps.com) Download Cracked Developers Applications For Free.url	239.00 B
0. Websites you may like/5. (Discuss.FTUForum.com) FTU Discussion Forum.url	294.00 B
0. Websites you may like/How you can help Team-FTU.txt	237.00 B
1. Introduction/1. Introduction.mp4	11.89 MB
1. Introduction/1. Introduction.vtt	2.12 kB
2. Backtracking/1. Backtracking introduction.mp4	14.41 MB
2. Backtracking/1. Backtracking introduction.vtt	6.79 kB
2. Backtracking/10. Knight tour implementation.mp4	21.08 MB
2. Backtracking/10. Knight tour implementation.vtt	9.74 kB
2. Backtracking/11. UPDATE Knight's Tour.html	716.00 B
2. Backtracking/12. Maze problem introduction.mp4	6.83 MB
2. Backtracking/12. Maze problem introduction.vtt	4.08 kB
2. Backtracking/13. Maze problem implementation.mp4	20.72 MB
2. Backtracking/13. Maze problem implementation.vtt	9.05 kB
2. Backtracking/14. NP-complete problems.mp4	9.01 MB
2. Backtracking/14. NP-complete problems.vtt	4.49 kB
2. Backtracking/2. N-queens problem introduction.mp4	22.60 MB
2. Backtracking/2. N-queens problem introduction.vtt	12.12 kB
2. Backtracking/3. N-queens problem implementation.mp4	29.04 MB
2. Backtracking/3. N-queens problem implementation.vtt	14.43 kB
2. Backtracking/4. Hamiltonian cycle introduction.mp4	21.71 MB
2. Backtracking/4. Hamiltonian cycle introduction.vtt	9.89 kB
2. Backtracking/5. Hamiltonian cycle illustration.mp4	13.19 MB
2. Backtracking/5. Hamiltonian cycle illustration.vtt	6.59 kB
2. Backtracking/6. Hamiltonian cycle implementation.mp4	24.79 MB
2. Backtracking/6. Hamiltonian cycle implementation.vtt	11.16 kB
2. Backtracking/7. Coloring problem introduction.mp4	22.01 MB
2. Backtracking/7. Coloring problem introduction.vtt	10.82 kB
2. Backtracking/8. Coloring problem implementation.mp4	17.49 MB
2. Backtracking/8. Coloring problem implementation.vtt	7.89 kB
2. Backtracking/9. Knight tour introduction.mp4	9.02 MB
2. Backtracking/9. Knight tour introduction.vtt	4.37 kB
3. Dynamic Programming/1. Dynamic programming introduction.mp4	8.58 MB
3. Dynamic Programming/1. Dynamic programming introduction.vtt	3.80 kB
3. Dynamic Programming/10. Rod cutting problem introduction.mp4	12.73 MB
3. Dynamic Programming/10. Rod cutting problem introduction.vtt	6.01 kB
3. Dynamic Programming/11. Rod cutting problem example.mp4	18.95 MB
3. Dynamic Programming/11. Rod cutting problem example.vtt	9.29 kB
3. Dynamic Programming/12. Rod cutting problem implementation.mp4	14.59 MB
3. Dynamic Programming/12. Rod cutting problem implementation.vtt	6.69 kB
3. Dynamic Programming/2. Fibonacci numbers introduction.mp4	13.42 MB
3. Dynamic Programming/2. Fibonacci numbers introduction.vtt	6.38 kB
3. Dynamic Programming/3. Fibonacci numbers implementation.mp4	11.98 MB
3. Dynamic Programming/3. Fibonacci numbers implementation.vtt	5.40 kB
3. Dynamic Programming/4. Knapsack problem introduction.mp4	31.23 MB
3. Dynamic Programming/4. Knapsack problem introduction.vtt	13.85 kB
3. Dynamic Programming/5. Knapsack problem example.mp4	30.08 MB
3. Dynamic Programming/5. Knapsack problem example.vtt	13.95 kB
3. Dynamic Programming/6. Knapsack problem implementation.mp4	18.71 MB
3. Dynamic Programming/6. Knapsack problem implementation.vtt	7.88 kB
3. Dynamic Programming/7. Coin change problem introduction.mp4	22.32 MB
3. Dynamic Programming/7. Coin change problem introduction.vtt	10.14 kB
3. Dynamic Programming/8. Coin change problem example.mp4	13.57 MB
3. Dynamic Programming/8. Coin change problem example.vtt	6.56 kB
3. Dynamic Programming/9. Coin change problem implementation.mp4	17.75 MB
3. Dynamic Programming/9. Coin change problem implementation.vtt	8.48 kB
4. Neural Network Theory/1. ---------- NEURAL NETWORKS INTRODUCTION ----------.html	35.00 B
4. Neural Network Theory/10. ---------- BACKPROPAGATION ----------.html	42.00 B
4. Neural Network Theory/11. Feedforward neural networks.mp4	18.41 MB
4. Neural Network Theory/11. Feedforward neural networks.vtt	8.88 kB
4. Neural Network Theory/12. Optimization - cost function.mp4	25.88 MB
4. Neural Network Theory/12. Optimization - cost function.vtt	11.85 kB
4. Neural Network Theory/13. Simplified feedforward network.mp4	19.41 MB
4. Neural Network Theory/13. Simplified feedforward network.vtt	9.03 kB
4. Neural Network Theory/14. Feedforward neural network topology.mp4	14.73 MB
4. Neural Network Theory/14. Feedforward neural network topology.vtt	6.56 kB
4. Neural Network Theory/15. The learning algorithm.mp4	13.25 MB
4. Neural Network Theory/15. The learning algorithm.vtt	6.03 kB
4. Neural Network Theory/16. Error calculation.mp4	13.73 MB
4. Neural Network Theory/16. Error calculation.vtt	6.51 kB
4. Neural Network Theory/17. Gradient calculation I - output layer.mp4	20.27 MB
4. Neural Network Theory/17. Gradient calculation I - output layer.vtt	9.29 kB
4. Neural Network Theory/18. Gradient calculation II - hidden layer.mp4	9.18 MB
4. Neural Network Theory/18. Gradient calculation II - hidden layer.vtt	4.09 kB
4. Neural Network Theory/19. Backpropagation.mp4	12.66 MB
4. Neural Network Theory/19. Backpropagation.vtt	5.72 kB
4. Neural Network Theory/2. Axons and neurons in the human brain.mp4	19.01 MB
4. Neural Network Theory/2. Axons and neurons in the human brain.vtt	9.37 kB
4. Neural Network Theory/20. Backpropagation II.mp4	4.67 MB
4. Neural Network Theory/20. Backpropagation II.vtt	2.00 kB
4. Neural Network Theory/21. Applications of neural networks I - character recognition.mp4	8.77 MB
4. Neural Network Theory/21. Applications of neural networks I - character recognition.vtt	4.43 kB
4. Neural Network Theory/22. Applications of neural networks II - stock market forecast.mp4	9.52 MB
4. Neural Network Theory/22. Applications of neural networks II - stock market forecast.vtt	4.69 kB
4. Neural Network Theory/23. Deep learning.mp4	9.46 MB
4. Neural Network Theory/23. Deep learning.vtt	4.58 kB
4. Neural Network Theory/3. Modeling human brain.mp4	16.05 MB
4. Neural Network Theory/3. Modeling human brain.vtt	8.36 kB
4. Neural Network Theory/4. Learning paradigms.mp4	6.40 MB
4. Neural Network Theory/4. Learning paradigms.vtt	3.07 kB
4. Neural Network Theory/5. Artificial neurons - the model.mp4	16.30 MB
4. Neural Network Theory/5. Artificial neurons - the model.vtt	7.27 kB
4. Neural Network Theory/6. Artificial neurons - activation functions.mp4	14.05 MB
4. Neural Network Theory/6. Artificial neurons - activation functions.vtt	6.58 kB
4. Neural Network Theory/7. Artificial neurons - an example.mp4	11.18 MB
4. Neural Network Theory/7. Artificial neurons - an example.vtt	4.60 kB
4. Neural Network Theory/8. Neural networks - the big picture.mp4	10.60 MB
4. Neural Network Theory/8. Neural networks - the big picture.vtt	4.88 kB
4. Neural Network Theory/9. Applications of neural networks.mp4	5.16 MB
4. Neural Network Theory/9. Applications of neural networks.vtt	2.37 kB
5. Neural Network Implementation/1. Neural network implementation - representations.mp4	10.11 MB
5. Neural Network Implementation/1. Neural network implementation - representations.vtt	4.87 kB
5. Neural Network Implementation/2. Neural network implementation - helper methods.mp4	8.14 MB
5. Neural Network Implementation/2. Neural network implementation - helper methods.vtt	3.79 kB
5. Neural Network Implementation/3. Neural network implementation - initialize.mp4	14.90 MB
5. Neural Network Implementation/3. Neural network implementation - initialize.vtt	5.82 kB
5. Neural Network Implementation/4. Neural network implementation - feedforward.mp4	13.43 MB
5. Neural Network Implementation/4. Neural network implementation - feedforward.vtt	5.37 kB
5. Neural Network Implementation/5. Neural network implementation - backpropagation.mp4	24.45 MB
5. Neural Network Implementation/5. Neural network implementation - backpropagation.vtt	8.79 kB
5. Neural Network Implementation/6. Neural network implementation - mean squared error.mp4	30.80 MB
5. Neural Network Implementation/6. Neural network implementation - mean squared error.vtt	3.94 kB
5. Neural Network Implementation/7. Neural network implementation - testing.mp4	68.41 MB
5. Neural Network Implementation/7. Neural network implementation - testing.vtt	5.86 kB
6. Course Materials (DOWNLOADS)/1. Course material.html	157.00 B
7. BONUS/1. DISCOUNT FOR OTHER COURSES!.html	3.73 kB

Description

For More Udemy Free Courses >>> https://ftuforum.com/
For more Lynda and other Courses >>> https://www.freecoursesonline.me/
Our Forum for discussion >>> https://discuss.ftuforum.com/

Learn recursion, backtracking (n-queens problem etc.) and dynamic programming (knapsack problem etc.)

BESTSELLER

Created by: Holczer Balazs
Last updated: 4/2019
Language: English
Caption (CC): Included
Torrent Contains: 119 Files, 8 Folders
Course Source: https://www.udemy.com/algorithmic-problems-in-python/

What you'll learn

• Understand backtracking
• Understand dynamic programming
• Solve problems from scratch
• Implement feedforward neural networks from scratch

Course content
all 40 lectures 04:04:05

Requirements

• Basic Python

Description

This course is about the fundamental concepts of algorithmic problems, focusing on recursion, backtracking and dynamic programming. As far as I am concerned these techniques are very important nowadays, algorithms can be used (and have several applications) in several fields from software engineering to investment banking or R&D.

Section 1:

• what is recursion
• stack memory and recursion
• factorial numbers problem
• Fibonacci numbers
• towers of Hanoi problem
• recursion vs iteration

Section 2:

• what is backtracking
• n-queens problem
• Hamiltonian cycle problem
• knight's tour problem
• coloring problem
• NP-complete problems

Section 3:

• what is dynamic programming
• Fibonacci numbers
• knapsack problem
• coin change problem
• rod cutting problem

In each section we will talk about the theoretical background for all of these algorithms then we are going to implement these problems one by one.

The first chapter is about recursion. Why is it crucial to know about recursion as a computer scientist? Why stack memory is crucial in recursion? We will consider several recursion related problems such as factorial problem or Fibonacci numbers. The second chapter is about backtracking: we will talk about problems such as n-queens problem or hamiltonian cycles and coloring problem. In the last chapter we will talk about dynamic programming, theory first then the concrete examples one by one: Fibonacci sequence problem and knapsack problem.

Thanks for joining the course, let's get started!

Who this course is for:

• This course is meant for newbies who are not familiar with algorithmic problems in the main or students looking for some refresher.