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TORRENT DETAILS

[GigaCourse.Com] Udemy - A Deep Understanding Of Deep Learning (with Python Intro)

TORRENT SUMMARY

	Status:	All the torrents in this section have been verified by our verification system
Category:	Other
Infohash	d7f7527973503ccb602b6dfd81ed0f16555b8fbe
Size:	22 GB in 93 files
Release Date(s):	Torrent Release: 13-02-2022 by user
Swarm:	0 Seeds & 0 Peers
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DESCRIPTION

A deep understanding of deep learning (with Python intro)

Master deep learning in PyTorch using an experimental scientific approach, with lots of examples and practice problems.

Created by Mike X Cohen
Last updated 1/2022
English
English [Auto]

For More Udemy Courses Visit: https://gigacourse.com
For More Courses Visit: https://Courseclub.me

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FILE LIST

Filename		Size
	01 - Introduction/001 How to learn from this course.mp4	55 MB
	01 - Introduction/001 How to learn from this course_en.srt	12.5 KB
	01 - Introduction/002 Using Udemy like a pro.mp4	54.4 MB
	01 - Introduction/002 Using Udemy like a pro_en.srt	11.8 KB
	02 - Download all course materials/001 Downloading and using the code.mp4	45.6 MB
	02 - Download all course materials/001 Downloading and using the code_en.srt	9.1 KB
	02 - Download all course materials/001 DUDL-PythonCode.zip	660.8 KB
	02 - Download all course materials/002 My policy on code-sharing.mp4	10.2 MB
	02 - Download all course materials/002 My policy on code-sharing_en.srt	2.4 KB
	03 - Concepts in deep learning/001 What is an artificial neural network.mp4	65.4 MB
	03 - Concepts in deep learning/001 What is an artificial neural network_en.srt	20.5 KB
	03 - Concepts in deep learning/002 How models learn.mp4	72.8 MB
	03 - Concepts in deep learning/002 How models learn_en.srt	18.1 KB
	03 - Concepts in deep learning/003 The role of DL in science and knowledge.mp4	34.8 MB
	03 - Concepts in deep learning/003 The role of DL in science and knowledge_en.srt	22.5 KB
	03 - Concepts in deep learning/004 Running experiments to understand DL.mp4	74.8 MB
	03 - Concepts in deep learning/004 Running experiments to understand DL_en.srt	18.5 KB
	03 - Concepts in deep learning/005 Are artificial neurons like biological neurons.mp4	114.7 MB
	03 - Concepts in deep learning/005 Are artificial neurons like biological neurons_en.srt	23.3 KB
	04 - About the Python tutorial/001 Should you watch the Python tutorial.mp4	23.8 MB
	04 - About the Python tutorial/001 Should you watch the Python tutorial_en.srt	5.9 KB
	05 - Math, numpy, PyTorch/001 PyTorch or TensorFlow.html	1.1 KB
	05 - Math, numpy, PyTorch/002 Introduction to this section.mp4	11.1 MB
	05 - Math, numpy, PyTorch/002 Introduction to this section_en.srt	2.8 KB
	05 - Math, numpy, PyTorch/003 Spectral theories in mathematics.mp4	51.1 MB
	05 - Math, numpy, PyTorch/003 Spectral theories in mathematics_en.srt	13.1 KB
	05 - Math, numpy, PyTorch/004 Terms and datatypes in math and computers.mp4	38.1 MB
	05 - Math, numpy, PyTorch/004 Terms and datatypes in math and computers_en.srt	10.3 KB
	05 - Math, numpy, PyTorch/005 Converting reality to numbers.mp4	33.2 MB
	05 - Math, numpy, PyTorch/005 Converting reality to numbers_en.srt	9.2 KB
	05 - Math, numpy, PyTorch/006 Vector and matrix transpose.mp4	37.7 MB
	05 - Math, numpy, PyTorch/006 Vector and matrix transpose_en.srt	9.6 KB
	05 - Math, numpy, PyTorch/007 OMG it's the dot product!.mp4	50.1 MB
	05 - Math, numpy, PyTorch/007 OMG it's the dot product!_en.srt	13.4 KB
	05 - Math, numpy, PyTorch/008 Matrix multiplication.mp4	85.7 MB
	05 - Math, numpy, PyTorch/008 Matrix multiplication_en.srt	19.8 KB
	05 - Math, numpy, PyTorch/009 Softmax.mp4	96 MB
	05 - Math, numpy, PyTorch/009 Softmax_en.srt	26.7 KB
	05 - Math, numpy, PyTorch/010 Logarithms.mp4	43.9 MB
	05 - Math, numpy, PyTorch/010 Logarithms_en.srt	11 KB
	05 - Math, numpy, PyTorch/011 Entropy and cross-entropy.mp4	106 MB
	05 - Math, numpy, PyTorch/011 Entropy and cross-entropy_en.srt	24.5 KB
	05 - Math, numpy, PyTorch/012 Minmax and argminargmax.mp4	88.2 MB
	05 - Math, numpy, PyTorch/012 Minmax and argminargmax_en.srt	17.5 KB
	05 - Math, numpy, PyTorch/013 Mean and variance.mp4	81.4 MB
	05 - Math, numpy, PyTorch/013 Mean and variance_en.srt	21.7 KB
	05 - Math, numpy, PyTorch/014 Random sampling and sampling variability.mp4	85.4 MB
	05 - Math, numpy, PyTorch/014 Random sampling and sampling variability_en.srt	15.8 KB
	05 - Math, numpy, PyTorch/015 Reproducible randomness via seeding.mp4	69.7 MB
	05 - Math, numpy, PyTorch/015 Reproducible randomness via seeding_en.srt	11.3 KB
	05 - Math, numpy, PyTorch/016 The t-test.mp4	81.4 MB
	05 - Math, numpy, PyTorch/016 The t-test_en.srt	18.7 KB
	05 - Math, numpy, PyTorch/017 Derivatives intuition and polynomials.mp4	80.3 MB
	05 - Math, numpy, PyTorch/017 Derivatives intuition and polynomials_en.srt	23.5 KB
	05 - Math, numpy, PyTorch/018 Derivatives find minima.mp4	45.5 MB
	05 - Math, numpy, PyTorch/018 Derivatives find minima_en.srt	11.7 KB
	05 - Math, numpy, PyTorch/019 Derivatives product and chain rules.mp4	55.6 MB
	05 - Math, numpy, PyTorch/019 Derivatives product and chain rules_en.srt	13 KB
	06 - Gradient descent/001 Overview of gradient descent.mp4	68.4 MB
	06 - Gradient descent/001 Overview of gradient descent_en.srt	20.1 KB
	06 - Gradient descent/002 What about local minima.mp4	67.1 MB
	06 - Gradient descent/002 What about local minima_en.srt	16.5 KB
	06 - Gradient descent/003 Gradient descent in 1D.mp4	119.3 MB
	06 - Gradient descent/003 Gradient descent in 1D_en.srt	23.8 KB
	06 - Gradient descent/004 CodeChallenge unfortunate starting value.mp4	77.1 MB
	06 - Gradient descent/004 CodeChallenge unfortunate starting value_en.srt	15.4 KB
	06 - Gradient descent/005 Gradient descent in 2D.mp4	96.4 MB
	06 - Gradient descent/005 Gradient descent in 2D_en.srt	20.7 KB
	06 - Gradient descent/006 CodeChallenge 2D gradient ascent.mp4	39.4 MB
	06 - Gradient descent/006 CodeChallenge 2D gradient ascent_en.srt	7.2 KB
	06 - Gradient descent/007 Parametric experiments on g.d.mp4	135.6 MB
	06 - Gradient descent/007 Parametric experiments on g.d_en.srt	26.2 KB
	06 - Gradient descent/008 CodeChallenge fixed vs. dynamic learning rate.mp4	113.6 MB
	06 - Gradient descent/008 CodeChallenge fixed vs. dynamic learning rate_en.srt	22.5 KB
	06 - Gradient descent/009 Vanishing and exploding gradients.mp4	30.2 MB
	06 - Gradient descent/009 Vanishing and exploding gradients_en.srt	8.7 KB
	06 - Gradient descent/010 Tangent Notebook revision history.mp4	9.9 MB
	06 - Gradient descent/010 Tangent Notebook revision history_en.srt	2.7 KB
	07 - ANNs (Artificial Neural Networks)/001 The perceptron and ANN architecture.mp4	85.8 MB
	07 - ANNs (Artificial Neural Networks)/001 The perceptron and ANN architecture_en.srt	26.9 KB
	07 - ANNs (Artificial Neural Networks)/002 A geometric view of ANNs.mp4	70.9 MB
	07 - ANNs (Artificial Neural Networks)/002 A geometric view of ANNs_en.srt	18.7 KB
	07 - ANNs (Artificial Neural Networks)/003 ANN math part 1 (forward prop).mp4	73.1 MB
	07 - ANNs (Artificial Neural Networks)/003 ANN math part 1 (forward prop)_en.srt	21.4 KB
	07 - ANNs (Artificial Neural Networks)/004 ANN math part 2 (errors, loss, cost).mp4	48.5 MB
	07 - ANNs (Artificial Neural Networks)/004 ANN math part 2 (errors, loss, cost)_en.srt	13.4 KB
	07 - ANNs (Artificial Neural Networks)/005 ANN math part 3 (backprop).mp4	52.9 MB
	07 - ANNs (Artificial Neural Networks)/005 ANN math part 3 (backprop)_en.srt	14.7 KB
	07 - ANNs (Artificial Neural Networks)/006 ANN for regression.mp4	135.5 MB
	07 - ANNs (Artificial Neural Networks)/006 ANN for regression_en.srt	34.5 KB
	07 - ANNs (Artificial Neural Networks)/007 CodeChallenge manipulate regression slopes.mp4	139.1 MB
	07 - ANNs (Artificial Neural Networks)/007 CodeChallenge manipulate regression slopes_en.srt	27.3 KB
	07 - ANNs (Artificial Neural Networks)/008 ANN for classifying qwerties.mp4	151.1 MB

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