Udemy Mathematics Behind Backpropagation Theory and Python Code BOOKWARE-BLZiSO | Apps-Tutorials | MP4 | 963.65 MiB
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.prouldy presents.
Mathematics Behind Backpropagation
Theory and Python Code
release date.: 20/09/26 disks........: 01
supplier.....: Bill os...........: Win
cracker......: Bill protection...: Bill
.;Program info;.
Unlock the secrets behind the algorithm that powers modern AI:
backpropagation. This essential concept drives the learning process
in neural networks, powering technologies like self-driving cars,
large language models (LLMs), medical imaging breakthroughs, and
much more.
In Mathematics Behind Backpropagation Theory and Code, we take you
on a journey from zero to mastery, exploring backpropagation through
both theory and hands-on implementation. Starting with the
fundamentals, you'll learn the mathematics behind backpropagation,
including derivatives, partial derivatives, and gradients. We'll
demystify gradient descent, showing you how machines optimize
themselves to improve performance efficiently.
But this isn't just about theoryyou'll roll up your sleeves and
implement backpropagation from scratch, first calculating everything
by hand to ensure you understand every step. Then, you'll move to Python
coding, building your own neural network without relying on any libraries
or pre-built tools. By the end, you'll know exactly how backpropagation
works, from the math to the code and beyond.
Whether you're an aspiring machine learning engineer, a developer
transitioning into AI, or a data scientist seeking deeper understanding,
this course equips you with rare skills most professionals don't have.
Master backpropagation, stand out in AI, and gain the confidence to build
neural networks with foundational knowledge that sets you apart in this
competitive field.
https://www.udemy.com/course/mathematics-behind-backpropagation-theory-and-python-code
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File List:
1.1G Mathematics Behind Backpropagation _ Theory and Python Code 34M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 1_What We're Going to Learn 34M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 1_What We're Going to Learn/1.What is this Course.mp4 8.0K Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 2_Course Resources 4.0K Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 2_Course Resources/2.Course Resources.html 655M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more 14M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/10.Understanding Gradients.mp4 35M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/11.Understanding What Partial Derivatives Do (Example).mp4 11M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/12.Introduction to Backpropagation.mp4 21M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/13.Understanding the Chain Rule (Optional).mp4 18M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/14.Gradient Derivation of the Mean Squared Error Loss Function.mp4 28M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/15.Visualizing the Loss Function + Gradients.mp4 55M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/16.Using the Chain rule to Calculate the Gradient of w2.mp4 12M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/17.Using the Chain Rule to Calculate the Gradient of w1.mp4 65M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/18.Visualizing Gradient Descent.mp4 18M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/19.Introduction to Gradient Descent.mp4 65M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/20.Understanding the Learning Rate (Alpha).mp4 13M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/21.Moving in the Opposite Direction of the Gradient.mp4 55M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/22.Calculating Gradient Descent by Hand.mp4 9.8M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/23.Coding our Simple Neural Network Part 1.mp4 19M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/24.Coding our Simple Neural Network Part 2.mp4 21M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/25.Coding our Simple Neural Network Part 3.mp4 33M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/26.Coding our Simple Neural Network Part 4.mp4 44M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/27.Coding our Simple Neural Network Part 5.mp4 17M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/3.Introduction to Our Simple Neural Network.mp4 20M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/4.Why We Use Computational Graphs.mp4 19M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/5.Conducting the Forward Pass.mp4 5.6M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/6.Roadmap to Understanding Backpropagation.mp4 11M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/7.Derivatives Theory.mp4 34M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/8.Numerical Example of Derivatives.mp4 22M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 3_Neural Networks, Derivatives, Gradients, Chain Rule, Gradient Descent and more/9.Understanding Partial Derivatives.mp4 402M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 4_Implementing Our Advanced Neural Network By Hand + Python 16M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 4_Implementing Our Advanced Neural Network By Hand + Python/28.Introduction to Our Advanced Neural Network.mp4 16M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 4_Implementing Our Advanced Neural Network By Hand + Python/29.Conducting the Forward Pass.mp4 17M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 4_Implementing Our Advanced Neural Network By Hand + Python/30.Getting Started with Backpropagation.mp4 28M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 4_Implementing Our Advanced Neural Network By Hand + Python/31.Getting the Derivative of the Sigmoid Activation Function (Optional).mp4 15M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 4_Implementing Our Advanced Neural Network By Hand + Python/32.Implementing Backpropagation with the Chain Rule.mp4 22M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 4_Implementing Our Advanced Neural Network By Hand + Python/33.Understanding How w3 Affects the Final Loss.mp4 41M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 4_Implementing Our Advanced Neural Network By Hand + Python/34.Calculating Gradients For Z1.mp4 26M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 4_Implementing Our Advanced Neural Network By Hand + Python/35.Understanding How w1 & w2 Affect the Loss.mp4 52M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 4_Implementing Our Advanced Neural Network By Hand + Python/36.Implementing Gradient Descent By Hand.mp4 41M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 4_Implementing Our Advanced Neural Network By Hand + Python/37.Coding our Advanced Neural Network Part (Implementing Forward Pass + Loss).mp4 58M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 4_Implementing Our Advanced Neural Network By Hand + Python/38.Coding our Advanced Neural Network Part 2 (Implement Backpropagation).mp4 18M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 4_Implementing Our Advanced Neural Network By Hand + Python/39.Coding our Advanced Neural Network Part 3 (Implement Gradient Descent).mp4 59M Mathematics Behind Backpropagation _ Theory and Python Code/Chapter 4_Implementing Our Advanced Neural Network By Hand + Python/40.Coding our Advanced Neural Network Part 4 (Training our Neural Network).mp4 1.1G total
File: 1.What is this Course.mp4 Size: 34762843 bytes (33.15 MiB), duration: 00:02:58, avg.bitrate: 1562 kb/s Audio: aac, 24000 Hz, stereo (und) Video: h264, yuv420p, 1920x1080, 30.00 fps(r) (und) Subtitles:
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