[GigaCourse.Com] Udemy - A deep understanding of deep learning (with Python intro)

• [GigaCourse.Com] Udemy - A deep understanding of deep learning (with Python intro)
• 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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