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[CourseClub.NET] Coursera - Introduction to Deep Learning
magnet:?xt=urn:btih:70e9796992bcbb00f65f3672ae86eb335593f36e&dn=[CourseClub.NET] Coursera - Introduction to Deep Learning
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文件列表详情
70e9796992bcbb00f65f3672ae86eb335593f36e
infohash:
39
文件数量
1.27 GB
文件大小
2019-7-31 19:08
创建日期
2024-10-5 15:39
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相关分词
CourseClub
NET
Coursera
-
Introduction
to
Deep
Learning
001.Specialization Promo/001. Welcome to AML specialization!.mp4 13.67 MB
002.Course intro/002. Course intro.mp4 22.1 MB
003.Linear model as the simplest neural network/003. Linear regression.mp4 35.73 MB
003.Linear model as the simplest neural network/004. Linear classification.mp4 42.66 MB
003.Linear model as the simplest neural network/005. Gradient descent.mp4 18.96 MB
004.Regularization in machine learning/006. Overfitting problem and model validation.mp4 26.42 MB
004.Regularization in machine learning/007. Model regularization.mp4 19.85 MB
005.Stochastic methods for optimization/008. Stochastic gradient descent.mp4 21.1 MB
005.Stochastic methods for optimization/009. Gradient descent extensions.mp4 36.57 MB
006.The simplest neural network MLP/010. Multilayer perceptron (MLP).mp4 44.68 MB
006.The simplest neural network MLP/011. Chain rule.mp4 26.59 MB
006.The simplest neural network MLP/012. Backpropagation.mp4 31.63 MB
007.Matrix derivatives/013. Efficient MLP implementation.mp4 47.09 MB
007.Matrix derivatives/014. Other matrix derivatives.mp4 21.42 MB
008.TensorFlow framework/015. What is TensorFlow.mp4 39.44 MB
008.TensorFlow framework/016. Our first model in TensorFlow.mp4 36.8 MB
009.Philosophy of deep learning/017. What Deep Learning is and is not.mp4 29.46 MB
009.Philosophy of deep learning/018. Deep learning as a language.mp4 24.6 MB
010.Introduction to CNN/019. Motivation for convolutional layers.mp4 41.38 MB
010.Introduction to CNN/020. Our first CNN architecture.mp4 42.57 MB
011.Modern CNNs/021. Training tips and tricks for deep CNNs.mp4 57.9 MB
011.Modern CNNs/022. Overview of modern CNN architectures.mp4 32.24 MB
012.Applications of CNNs/023. Learning new tasks with pre-trained CNNs.mp4 19.28 MB
012.Applications of CNNs/024. A glimpse of other Computer Vision tasks.mp4 30.74 MB
013.Intro to Unsupervised Learning/025. Unsupervised learning what it is and why bother.mp4 23.78 MB
013.Intro to Unsupervised Learning/026. Autoencoders 101.mp4 22.14 MB
014.More Autoencoders/027. Autoencoder applications.mp4 40.85 MB
014.More Autoencoders/028. Autoencoder applications image generation, data visualization & more.mp4 28.21 MB
015.Word Embeddings/029. Natural language processing primer.mp4 36.68 MB
015.Word Embeddings/030. Word embeddings.mp4 48.35 MB
016.Generative Adversarial Networks/031. Generative models 101.mp4 26.68 MB
016.Generative Adversarial Networks/032. Generative Adversarial Networks.mp4 36.16 MB
016.Generative Adversarial Networks/033. Applications of adversarial approach.mp4 41.89 MB
017.Introduction to RNN/034. Motivation for recurrent layers.mp4 30.15 MB
017.Introduction to RNN/035. Simple RNN and Backpropagation.mp4 35.07 MB
018.Modern RNNs/036. The training of RNNs is not that easy.mp4 26.39 MB
018.Modern RNNs/037. Dealing with vanishing and exploding gradients.mp4 34.86 MB
018.Modern RNNs/038. Modern RNNs LSTM and GRU.mp4 47.7 MB
019.Applications of RNNs/039. Practical use cases for RNNs.mp4 56.12 MB
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