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- 【文档书籍】 Рашка С., Лю Ю. (Хэйден), Мирджалили В. - Машинное обучение с PyTorch и Scikit-Learn (Взгляд экспертов) - 2023.pdf
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Рашка С., Лю Ю. (Хэйден), Мирджалили В. - Машинное обучение с PyTorch и Scikit-Learn (Взгляд экспертов) - 2023.pdf 89.7 MB
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- 【影视】 [ FreeCourseWeb.com ] Pytorch - Advanced Deep Learning (Computer Vision, DataAug)
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~Get Your Files Here !/02 Data Science in Numpy & Pytorch (code) - Background/001 Data Science in Numpy - Part1 (Code).mp4 123.5 MB
~Get Your Files Here !/13 SupCon & SimCLR (Code)/002 Mocking SimCLR(Code).mp4 60.4 MB
~Get Your Files Here !/05 SOTA Data augmentation (Hands On)/005 CutMix (Code).mp4 57.2 MB
~Get Your Files Here !/04 Faiss & Image Search (Hands on)/001 Image Search(Basic & Cluster).mp4 56.5 MB
~Get Your Files Here !/11 PEARL and NPILD (code)/001 NCE & Memory Bank (Code).mp4 55.8 MB
~Get Your Files Here !/03 Pytorch AutoGrad/001 Pytorch AutoGrad.mp4 47.1 MB
~Get Your Files Here !/13 SupCon & SimCLR (Code)/003 SimClr and Supervised Contrastive Learning (Code).mp4 47.0 MB
~Get Your Files Here !/11 PEARL and NPILD (code)/002 Network and Training NPILD & Pearl (Code).mp4 42.2 MB
~Get Your Files Here !/09 Non-Parametric Instance Level Discrimination(NPILD) (hands on)/001 Non-Parametric Instance-level Discrimination & Metric learning approach.mp4 41.2 MB
~Get Your Files Here !/01 Introduction/001 Why Should You Take This Course_.mp4 36.4 MB
~Get Your Files Here !/04 Faiss & Image Search (Hands on)/004 Basic Image Search With pertained Resnet (cifar-10 dataset) (Code).mp4 34.1 MB
~Get Your Files Here !/04 Faiss & Image Search (Hands on)/003 Basic Image Search (Code).mp4 34.0 MB
~Get Your Files Here !/02 Data Science in Numpy & Pytorch (code) - Background/003 Data Science in Pytorch - Part 2(Code).mp4 34.0 MB
~Get Your Files Here !/13 SupCon & SimCLR (Code)/001 Supervised Contrastive Learning.mp4 32.5 MB
~Get Your Files Here !/01 Introduction/003 Applications.mp4 31.9 MB
~Get Your Files Here !/03 Pytorch AutoGrad/002 Custom CNN in Pytorch.mp4 31.7 MB
~Get Your Files Here !/10 PEARL/004 PEARL Results.mp4 31.7 MB
~Get Your Files Here !/15 Bonus Lectures/001 Vissl & Albumentations.mp4 31.6 MB
~Get Your Files Here !/05 SOTA Data augmentation (Hands On)/006 RandAugment.mp4 30.2 MB
~Get Your Files Here !/09 Non-Parametric Instance Level Discrimination(NPILD) (hands on)/008 Non Parametric Softmax (CrossEntropy) (Code).mp4 30.0 MB
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~Get Your Files Here !/5. Coding deep neural networks in PyTorch and PyTorch Lightning/9. Train an MNIST model using PyTorch Lightning II.mp4 124.2 MB
~Get Your Files Here !/5. Coding deep neural networks in PyTorch and PyTorch Lightning/10. Next steps.mp4 115.9 MB
~Get Your Files Here !/5. Coding deep neural networks in PyTorch and PyTorch Lightning/7. Train an MNIST model using PyTorch's nn module II.mp4 107.1 MB
~Get Your Files Here !/5. Coding deep neural networks in PyTorch and PyTorch Lightning/4. Train an MNIST model from scratch in plain PyTorch III.mp4 107.0 MB
~Get Your Files Here !/3. How the model learns on its own - Back Propagation algorithm deep-div/4. Gradient descent.mp4 105.9 MB
~Get Your Files Here !/5. Coding deep neural networks in PyTorch and PyTorch Lightning/3. Train an MNIST model from scratch in plain PyTorch II.mp4 101.0 MB
~Get Your Files Here !/5. Coding deep neural networks in PyTorch and PyTorch Lightning/2. Train an MNIST model from scratch in plain PyTorch I.mp4 100.9 MB
~Get Your Files Here !/5. Coding deep neural networks in PyTorch and PyTorch Lightning/6. Train an MNIST model using PyTorch's nn module I.mp4 89.1 MB
~Get Your Files Here !/5. Coding deep neural networks in PyTorch and PyTorch Lightning/8. Train an MNIST model using PyTorch Lightning I.mp4 87.0 MB
~Get Your Files Here !/3. How the model learns on its own - Back Propagation algorithm deep-div/11. Computational graph IV - backward pass III.mp4 86.8 MB
~Get Your Files Here !/5. Coding deep neural networks in PyTorch and PyTorch Lightning/5. Train an MNIST model from scratch in plain PyTorch IV.mp4 79.3 MB
~Get Your Files Here !/1. Deep learning - the big picture/1. Introduction.mp4 75.5 MB
~Get Your Files Here !/3. How the model learns on its own - Back Propagation algorithm deep-div/10. Computational graph III - backward pass II.mp4 66.6 MB
~Get Your Files Here !/3. How the model learns on its own - Back Propagation algorithm deep-div/9. Computational graph II - backward pass.mp4 50.4 MB
~Get Your Files Here !/3. How the model learns on its own - Back Propagation algorithm deep-div/12. Forward and backward pass recap and wrap up.mp4 48.2 MB
~Get Your Files Here !/2. Reinventing deep neural network from scratch/3. Network view.mp4 47.6 MB
~Get Your Files Here !/4. How to make neural networks work in reality/8. Batch normalization.mp4 46.0 MB
~Get Your Files Here !/3. How the model learns on its own - Back Propagation algorithm deep-div/5. Calculus detour - partial derivatives and gradient descent.mp4 44.2 MB
~Get Your Files Here !/4. How to make neural networks work in reality/4. Stochastic and mini-batch gradient descent.mp4 41.6 MB
~Get Your Files Here !/4. How to make neural networks work in reality/1. Vanishing gradient problem.mp4 40.2 MB
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~Get Your Files Here !/3. GAN with Pytorch/1. Introduction.mp4 180.7 MB
~Get Your Files Here !/1. Introduction/6. Simple Neural Network with Pytorch Implementation Part 1.mp4 166.7 MB
~Get Your Files Here !/4. NLP with Pytorch/3. Recurrent Neural Network Part 1 Explanation.mp4 165.5 MB
~Get Your Files Here !/1. Introduction/7. Simple Neural Network with Pytorch Implementation Part 2.mp4 156.2 MB
~Get Your Files Here !/2. Image Processing with Pytorch/5. Project Time MNIST Implementation Part 1 Importing libraries and data.mp4 155.9 MB
~Get Your Files Here !/2. Image Processing with Pytorch/10. Project Time MNIST Implementation Part 6.mp4 152.0 MB
~Get Your Files Here !/2. Image Processing with Pytorch/9. Project Time MNIST Implementation Part 5.mp4 137.9 MB
~Get Your Files Here !/3. GAN with Pytorch/6. GAN Project Fully Connected Network and results.mp4 136.6 MB
~Get Your Files Here !/3. GAN with Pytorch/4. GAN Project Discriminator Construction.mp4 116.3 MB
~Get Your Files Here !/5. Reinforcement with Pytorch/3. Introduction to the agent, environment, action and observation.mp4 105.9 MB
~Get Your Files Here !/3. GAN with Pytorch/3. GAN Project Generator Construction.mp4 103.8 MB
~Get Your Files Here !/5. Reinforcement with Pytorch/12. Cart Pole Implementation Part 2.mp4 100.8 MB
~Get Your Files Here !/4. NLP with Pytorch/9. Language Model Implementation Part 1.mp4 97.7 MB
~Get Your Files Here !/5. Reinforcement with Pytorch/16. Developing hill climbing part 2.mp4 97.3 MB
~Get Your Files Here !/4. NLP with Pytorch/2. Recurrent Neural Network Implementation Part 1.mp4 95.7 MB
~Get Your Files Here !/4. NLP with Pytorch/4. Recurrent Neural Network Implementation Part 2.mp4 95.5 MB
~Get Your Files Here !/5. Reinforcement with Pytorch/9. Reinforcement Learning Algorithm.mp4 94.6 MB
~Get Your Files Here !/4. NLP with Pytorch/10. Language Model Implementation Part 1 (Explanation).mp4 94.1 MB
~Get Your Files Here !/4. NLP with Pytorch/8. LSTMs Implementation Part 1 Explanation and final implementation.mp4 92.2 MB
~Get Your Files Here !/2. Image Processing with Pytorch/7. Project Time MNIST Implementation Part 3.mp4 86.8 MB
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03 - Working with Classes and Tensors/01 - Classes.mp4 51.3 MB
04 - Working with Loss, Autograd, and Optimizers/01 - Loss.mp4 43.4 MB
02 - Fashion MNIST and Neural Networks/01 - Working with the Fashion MNIST dataset.mp4 34.8 MB
05 - Troubleshooting and CPUGPU Usage/02 - CPU to GPU.mp4 15.5 MB
06 - Conclusion/01 - Future project ideas.mp4 15.1 MB
05 - Troubleshooting and CPUGPU Usage/01 - Troubleshooting.mp4 12.0 MB
04 - Working with Loss, Autograd, and Optimizers/02 - Autograd.mp4 11.3 MB
02 - Fashion MNIST and Neural Networks/02 - Neural network intuition.mp4 11.1 MB
04 - Working with Loss, Autograd, and Optimizers/05 - Using optimizers.mp4 10.5 MB
01 - Introduction/01 - Welcome.mp4 9.9 MB
04 - Working with Loss, Autograd, and Optimizers/03 - Autograd with tensors.mp4 9.4 MB
05 - Troubleshooting and CPUGPU Usage/03 - Validation.mp4 8.1 MB
03 - Working with Classes and Tensors/02 - Tensors.mp4 7.6 MB
03 - Working with Classes and Tensors/03 - Training the network.mp4 5.9 MB
01 - Introduction/02 - What you should know before watching this course.mp4 4.0 MB
04 - Working with Loss, Autograd, and Optimizers/04 - Optimizers.mp4 3.0 MB
05 - Troubleshooting and CPUGPU Usage/02 - CPU to GPU.srt 9.3 kB
02 - Fashion MNIST and Neural Networks/02 - Neural network intuition.srt 9.1 kB
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Part 01-Module 01-Lesson 03_Talking PyTorch with Soumith Chintala/01. Origins Of PyTorch V2-0eLXNFv6aT8.mp4 31.5 MB
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Part 01-Module 01-Lesson 07_Recurrent Neural Networks/20. 07 CharRNN Solution V1-ed33qePHrJM.mp4 19.2 MB
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Part 01-Module 01-Lesson 04_Introduction to PyTorch/08. PyTorch V2 Part 2 Solution 2 V1-8KRX7HvqfP0.mp4 17.5 MB
Part 01-Module 01-Lesson 07_Recurrent Neural Networks/17. 04 Implementing CharRNN V2-MMtgZXzFB10.mp4 17.2 MB
Part 01-Module 01-Lesson 03_Talking PyTorch with Soumith Chintala/05. Cutting-Edge Applicationns In PyTorch-s8p6vqOubqw.mp4 16.6 MB
Part 01-Module 01-Lesson 04_Introduction to PyTorch/15. PyTorch V2 Part 5 Solution V1-AjrXltxqsK4.mp4 16.6 MB
Part 01-Module 01-Lesson 04_Introduction to PyTorch/17. PyTorch - Part 6-3ZJfo2bR-uw.mp4 16.6 MB
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- 【文档书籍】 Machine Learning with PyTorch and Scikit-Learn
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