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| [TGx]Downloaded from torrentgalaxy.org.txt |
524б |
| 01. 01 StyleTransfer V3-_urN9BQ7RHM.en.vtt |
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| 01. 01 StyleTransfer V3-_urN9BQ7RHM.mp4 |
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| 01. 01 StyleTransfer V3-_urN9BQ7RHM.pt-BR.vtt |
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| 01. 1 SentimentRNN Intro V1-bQWUuaMc9ZI.en.vtt |
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| 01. 1 SentimentRNN Intro V1-bQWUuaMc9ZI.mp4 |
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| 01. Final project.html |
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| 01. Introducing Alexis.html |
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| 01. Introducing Alexis-38ExGpdyvJI.en.vtt |
694б |
| 01. Introducing Alexis-38ExGpdyvJI.mp4 |
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| 01. Introducing Alexis-38ExGpdyvJI.pt-BR.vtt |
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| 01. Introducing Alexis-38ExGpdyvJI.zh-CN.vtt |
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| 01. Introduction.html |
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| 01. Introduction-tn-CrUTkCUc.en.vtt |
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| 01. Introduction-tn-CrUTkCUc.mp4 |
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| 01. Introduction-tn-CrUTkCUc.pt-BR.vtt |
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| 01. Introduction-tn-CrUTkCUc.zh-CN.vtt |
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| 01. Intro to RNNs.html |
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| 01. Origins of PyTorch.html |
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| 01. Origins Of PyTorch V2-0eLXNFv6aT8.mp4 |
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| 01. Sentiment RNN, Introduction.html |
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| 01. Style Transfer.html |
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| 01. Welcome!.html |
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| 01. Welcome!.html |
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| 01. Welcome to the course!.html |
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| 02. 02 SeparatingStyleandContent V2-PNFFAhymuHc.en.vtt |
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| 02. 02 SeparatingStyleandContent V2-PNFFAhymuHc.mp4 |
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| 02. 02 SeparatingStyleandContent V2-PNFFAhymuHc.pt-BR.vtt |
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| 02. Applications of CNNs.html |
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| 02. Applications of CNNs-HrYNL_1SV2Y.en.vtt |
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| 02. Applications of CNNs-HrYNL_1SV2Y.mp4 |
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| 02. Applications of CNNs-HrYNL_1SV2Y.pt-BR.vtt |
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| 02. Applications of CNNs-HrYNL_1SV2Y.zh-CN.vtt |
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| 02. Classification Problems 1.html |
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| 02. Classsification Example-Dh625piH7Z0.en.vtt |
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| 02. Classsification Example-Dh625piH7Z0.mp4 |
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| 02. Classsification Example-Dh625piH7Z0.pt-BR.vtt |
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| 02. Classsification Example-Dh625piH7Z0.zh-CN.vtt |
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| 02. Debugging and Designing PyTorch.html |
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| 02. Debugging And Designing PyTorch-Nn8140ECzPU.mp4 |
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| 02. Installing PyTorch 1.0.html |
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| 02. Instructors.html |
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| 02. PyTorch 10 Install V1-kIwKPxgReFY.mp4 |
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| 02. PyTorch V2 Part 1 V1-6Z7WntXays8.en.vtt |
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| 02. PyTorch V2 Part 1 V1-6Z7WntXays8.mp4 |
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| 02. RNN vs LSTM.html |
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| 02. RNN Vs LSTM-70MgF-IwAr8.en.vtt |
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| 02. RNN Vs LSTM-70MgF-IwAr8.mp4 |
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| 02. RNN Vs LSTM-70MgF-IwAr8.zh-CN.vtt |
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| 02. Sentiment Analysis RNNs.html |
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| 02. Separating Style & Content.html |
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| 02. Single layer neural networks.html |
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| 03. 03 ContentRepandStyleTransfer V3-PQ1UuzOIjCM.en.vtt |
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| 03. 03 ContentRepandStyleTransfer V3-PQ1UuzOIjCM.mp4 |
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| 03. 03 ContentRepandStyleTransfer V3-PQ1UuzOIjCM.pt-BR.vtt |
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| 03. Basics of LSTM.html |
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| 03. Classification Example-46PywnGa_cQ.en.vtt |
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| 03. Classification Example-46PywnGa_cQ.mp4 |
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| 03. Classification Example-46PywnGa_cQ.pt-BR.vtt |
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| 03. Classification Example-46PywnGa_cQ.zh-CN.vtt |
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| 03. Classification Problems 2.html |
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| 03. ConNet 01 LessonOutline V1 V1-77LzWE1qQrc.en.vtt |
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| 03. ConNet 01 LessonOutline V1 V1-77LzWE1qQrc.mp4 |
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| 03. ConNet 01 LessonOutline V1 V1-77LzWE1qQrc.pt-BR.vtt |
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| 03. Course Outline.html |
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| 03. From Research to Production.html |
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| 03. From Research To Production-eCysOAw8azs.mp4 |
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| 03. Lesson Outline.html |
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| 03. LSTM Basics-gjb68a4XsqE.en.vtt |
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| 03. LSTM Basics-gjb68a4XsqE.mp4 |
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| 03. LSTM Basics-gjb68a4XsqE.pt-BR.vtt |
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| 03. LSTM Basics-gjb68a4XsqE.zh-CN.vtt |
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| 03. Notebook Sentiment RNN.html |
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| 03. PyTorch for Production.html |
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| 03. PyTorch For Production V1-DBSoZWd4lQo.mp4 |
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| 03. PyTorch V2 Part 1 Solution V1-mNJ8CujTtpo.en.vtt |
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| 03. PyTorch V2 Part 1 Solution V1-mNJ8CujTtpo.mp4 |
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| 03. Single layer neural networks solution.html |
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| 03. VGG19 & Content Loss.html |
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| 04. 3 Data PreProcessing V1-Xw1MWmql7no.en.vtt |
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| 04. 3 Data PreProcessing V1-Xw1MWmql7no.mp4 |
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| 04. 41 GramMatrixStyleTransfer V3-e718uVAW3KU.en.vtt |
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| 04. 41 GramMatrixStyleTransfer V3-e718uVAW3KU.mp4 |
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| 04. 41 GramMatrixStyleTransfer V3-e718uVAW3KU.pt-BR.vtt |
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| 04. Architecture of LSTM.html |
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| 04. ConNet 021 MNISTClassification V1 V2-a7bvIGZpcnk.en.vtt |
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| 04. ConNet 021 MNISTClassification V1 V2-a7bvIGZpcnk.mp4 |
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| 04. ConNet 021 MNISTClassification V1 V2-a7bvIGZpcnk.pt-BR.vtt |
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| 04. Data Pre-Processing.html |
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| 04. Gram Matrix.html |
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| 04. How this program works.html |
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| 04. Hybrid Frontend.html |
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| 04. Hybrid Frontend And JIT Compiler-J4z-P8yUZu4.mp4 |
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| 04. Linear Boundaries.html |
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| 04. Linear Boundaries-X-uMlsBi07k.en.vtt |
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| 04. Linear Boundaries-X-uMlsBi07k.mp4 |
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| 04. Linear Boundaries-X-uMlsBi07k.pt-BR.vtt |
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| 04. Linear Boundaries-X-uMlsBi07k.zh-CN.vtt |
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| 04. LSTM Architecture-ycwthhdx8ws.en.vtt |
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| 04. LSTM Architecture-ycwthhdx8ws.mp4 |
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| 04. LSTM Architecture-ycwthhdx8ws.pt-BR.vtt |
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| 04. LSTM Architecture-ycwthhdx8ws.zh-CN.vtt |
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| 04. MNIST Dataset.html |
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| 04. Networks Using Matrix Multiplication.html |
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| 04. PyTorch Script Tracing V1-lYmQDUprQa0.mp4 |
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| 04. PyTorch V2 Part 1 Solution 2 V1-QLaGMz8Ca3E.en.vtt |
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| 04. PyTorch V2 Part 1 Solution 2 V1-QLaGMz8Ca3E.mp4 |
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| 04. Torch Script & Tracing.html |
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| 05. 09 Higher Dimensions-eBHunImDmWw.en.vtt |
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| 05. 09 Higher Dimensions-eBHunImDmWw.mp4 |
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| 05. 09 Higher Dimensions-eBHunImDmWw.pt-BR.vtt |
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| 05. 09 Higher Dimensions-eBHunImDmWw.zh-CN.vtt |
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| 05. 42 StyleLossStyleTransfer V2-VazrQ7u-OHo.en.vtt |
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| 05. 42 StyleLossStyleTransfer V2-VazrQ7u-OHo.mp4 |
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| 05. 42 StyleLossStyleTransfer V2-VazrQ7u-OHo.pt-BR.vtt |
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| 05. 4 EncodingWords Sol V1-4RYyn3zv1Hg.en.vtt |
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| 05. 4 EncodingWords Sol V1-4RYyn3zv1Hg.mp4 |
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| 05. Annotations.html |
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| 05. ConNet 022 How Computers Interpret Images V1-mEPfoM68Fx4.en.vtt |
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| 05. ConNet 022 How Computers Interpret Images V1-mEPfoM68Fx4.mp4 |
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| 05. ConNet 022 How Computers Interpret Images V1-mEPfoM68Fx4.pt-BR.vtt |
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| 05. Cutting-Edge Applicationns In PyTorch-s8p6vqOubqw.mp4 |
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| 05. Cutting-edge Applications in PyTorch.html |
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| 05. Encoding Words, Solution.html |
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| 05. Higher Dimensions.html |
10.42Кб |
| 05. How Computers Interpret Images.html |
10.76Кб |
| 05. Join the Scholar Learning Community.html |
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| 05. Learn Gate-aVHVI7ovbHY.en.vtt |
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| 05. Learn Gate-aVHVI7ovbHY.mp4 |
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| 05. Learn Gate-aVHVI7ovbHY.pt-BR.vtt |
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| 05. Learn Gate-aVHVI7ovbHY.zh-CN.vtt |
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| 05. Multilayer Networks Solution.html |
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| 05. PyTorch Script Annotation V2-pO1RM7mKaFg.mp4 |
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| 05. PyTorch V2 Part 1 Solution 3 V1-iMIo9p5iSbE.en.vtt |
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| 05. PyTorch V2 Part 1 Solution 3 V1-iMIo9p5iSbE.mp4 |
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| 05. Style Loss.html |
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| 05. The Learn Gate.html |
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| 06. 05 LossWeightsStyleTransfer V2-qO8oiZBtG1I.en.vtt |
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| 06. 05 LossWeightsStyleTransfer V2-qO8oiZBtG1I.mp4 |
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| 06. 05 LossWeightsStyleTransfer V2-qO8oiZBtG1I.pt-BR.vtt |
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| 06. 5 GettingRid ZeroLength V1-Hs6ithuvDJg.en.vtt |
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| 06. 5 GettingRid ZeroLength V1-Hs6ithuvDJg.mp4 |
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| 06. ConNet 03 MLPStructure&ClassScore V1 V1-fP0Odiai8sk.en.vtt |
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| 06. ConNet 03 MLPStructure&ClassScore V1 V1-fP0Odiai8sk.mp4 |
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| 06. ConNet 03 MLPStructure&ClassScore V1 V1-fP0Odiai8sk.pt-BR.vtt |
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| 06. DL 06 Perceptron Definition Fix V2-hImSxZyRiOw.en.vtt |
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| 06. DL 06 Perceptron Definition Fix V2-hImSxZyRiOw.mp4 |
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| 06. DL 06 Perceptron Definition Fix V2-hImSxZyRiOw.pt-BR.vtt |
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| 06. DL 06 Perceptron Definition Fix V2-hImSxZyRiOw.zh-CN.vtt |
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| 06. Forget Gate-iWxpfxLUPSU.en.vtt |
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| 06. Forget Gate-iWxpfxLUPSU.mp4 |
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| 06. Forget Gate-iWxpfxLUPSU.zh-CN.vtt |
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| 06. Getting Rid of Zero-Length.html |
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| 06. Loss Weights.html |
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| 06. MLP Structure & Class Scores.html |
9.49Кб |
| 06. Neural Networks in PyTorch.html |
6.32Кб |
| 06. Perceptrons.html |
10.35Кб |
| 06. PyTorch C++ API.html |
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| 06. PyTorch C API V2-P1S1dN1gHmw.mp4 |
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| 06. PyTorch V2 Part 2 V1-CSQOdOb2mlg.en.vtt |
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| 06. PyTorch V2 Part 2 V1-CSQOdOb2mlg.mp4 |
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| 06. Scholarship Challenge Project.html |
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| 06. The Forget Gate.html |
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| 06. User Needs and Adding Features.html |
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| 06. User Needs And Adding Features-7HH65_c7Acw.mp4 |
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| 07. 04 Do Your Research V1-CR4JeAn1fgk.en.vtt |
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| 07. 04 Do Your Research V1-CR4JeAn1fgk.mp4 |
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| 07. 04 Do Your Research V1-CR4JeAn1fgk.pt-BR.vtt |
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| 07. 6 Cleaning And Padding V1-UgPo1_cq-0g.en.vtt |
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| 07. 6 Cleaning And Padding V1-UgPo1_cq-0g.mp4 |
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| 07. 6 VGG Features V1-Q5N2NEv7ADc.en.vtt |
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| 07. 6 VGG Features V1-Q5N2NEv7ADc.mp4 |
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| 07. 6 VGG Features V1-Q5N2NEv7ADc.pt-BR.vtt |
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| 07. Cleaning & Padding Data.html |
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| 07. Do Your Research.html |
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| 07. Neural Networks Solution.html |
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| 07. PyTorch and the Facebook Product.html |
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| 07. PyTorch And The Facebook Product-TjVveb0iVrA.mp4 |
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| 07. PyTorch V2 Part 2 Solution V1-zym36ihtOMY.en.vtt |
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| 07. PyTorch V2 Part 2 Solution V1-zym36ihtOMY.mp4 |
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| 07. Remember Gate-0qlm86HaXuU.en.vtt |
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| 07. Remember Gate-0qlm86HaXuU.mp4 |
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| 07. Remember Gate-0qlm86HaXuU.pt-BR.vtt |
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| 07. Remember Gate-0qlm86HaXuU.zh-CN.vtt |
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| 07. The Remember Gate.html |
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| 07. VGG Features.html |
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| 07. Want to learn more.html |
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| 07. Why Neural Networks.html |
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| 07. Why Neural Networks-zAkzOZntK6Y.en.vtt |
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| 07. Why Neural Networks-zAkzOZntK6Y.mp4 |
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| 07. Why Neural Networks-zAkzOZntK6Y.zh-CN.vtt |
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| 08. 7 PaddedFeatures Sol V1-sYOd1IDmep8.en.vtt |
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| 08. 7 PaddedFeatures Sol V1-sYOd1IDmep8.mp4 |
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| 08. AND And OR Perceptrons-45K5N0P9wJk.en.vtt |
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| 08. AND And OR Perceptrons-45K5N0P9wJk.mp4 |
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| 08. ConNet 05 Loss&Optimization V1 V3-BmPDtSXv18w.en.vtt |
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| 08. ConNet 05 Loss&Optimization V1 V3-BmPDtSXv18w.pt-BR.vtt |
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| 08. Implementing Softmax Solution.html |
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| 08. Loss & Optimization.html |
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| 08. LSTM 7 Use Gate-5Ifolm1jTdY.en.vtt |
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| 08. Notebook Style Transfer.html |
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| 08. Padded Features, Solution.html |
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| 08. Perceptrons as Logical Operators.html |
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| 08. PyTorch V2 Part 2 Solution 2 V1-8KRX7HvqfP0.mp4 |
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| 08. The Future of PyTorch.html |
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| 08. The Future Of PyTorch-vfCg3FoOjE4.mp4 |
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| 08. The Use Gate.html |
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| 09. 06 Defining A Network V1-9gvaQvyfLfY.en.vtt |
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| 09. 07 Perceptron Algorithm Trick-lif_qPmXvWA.en.vtt |
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| 09. 7 Feats Gram Matrix V1-f89x9oAh6X0.en.vtt |
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| 09. 8 TensorDataset Batching V1-Oxuf2QIPjj4.en.vtt |
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| 09. 8 TensorDataset Batching V1-Oxuf2QIPjj4.mp4 |
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| 09. Defining a Network in PyTorch.html |
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| 09. DL 10 S Perceptron Algorithm-fATmrG2hQzI.en.vtt |
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| 09. DL 10 S Perceptron Algorithm-fATmrG2hQzI.mp4 |
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| 09. Features & Gram Matrix.html |
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| 09. Learning Ai-NMItGw0GFGM.mp4 |
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| 09. Learning More in AI.html |
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| 09. Network Architectures in PyTorch.html |
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| 09. Perceptron Trick.html |
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| 09. Putting it All Together.html |
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| 10. Defining the Model.html |
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