[CourseClub NET] Coursera - Introduction to Deep Learning
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[CourseClub NET] Coursera - Introduction to Deep Learning
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Torrent File Content (81 files)
[CourseClub.NET] Coursera - Introduction to Deep Learning
001.Specialization Promo
001. Welcome to AML specialization!.mp4 -
001.Specialization Promo
001. Welcome to AML specialization!.mp4 -
13.67 MB
001. Welcome to AML specialization!.srt -
4.71 KB
002.Course intro
002. Course intro.mp4 -
002. Course intro.mp4 -
22.1 MB
002. Course intro.srt -
8.78 KB
003.Linear model as the simplest neural network
003. Linear regression.mp4 -
003. Linear regression.mp4 -
35.73 MB
003. Linear regression.srt -
13.34 KB
004. Linear classification.mp4 -
42.66 MB
004. Linear classification.srt -
16.39 KB
005. Gradient descent.mp4 -
18.96 MB
005. Gradient descent.srt -
7.41 KB
004.Regularization in machine learning
006. Overfitting problem and model validation.mp4 -
006. Overfitting problem and model validation.mp4 -
26.42 MB
006. Overfitting problem and model validation.srt -
9.79 KB
007. Model regularization.mp4 -
19.85 MB
007. Model regularization.srt -
7.43 KB
005.Stochastic methods for optimization
008. Stochastic gradient descent.mp4 -
008. Stochastic gradient descent.mp4 -
21.1 MB
008. Stochastic gradient descent.srt -
7.76 KB
009. Gradient descent extensions.mp4 -
36.57 MB
009. Gradient descent extensions.srt -
13.38 KB
006.The simplest neural network MLP
010. Multilayer perceptron (MLP).mp4 -
010. Multilayer perceptron (MLP).mp4 -
44.68 MB
010. Multilayer perceptron (MLP).srt -
18.51 KB
011. Chain rule.mp4 -
26.59 MB
011. Chain rule.srt -
9.97 KB
012. Backpropagation.mp4 -
31.63 MB
012. Backpropagation.srt -
11.37 KB
007.Matrix derivatives
013. Efficient MLP implementation.mp4 -
013. Efficient MLP implementation.mp4 -
47.09 MB
013. Efficient MLP implementation.srt -
16.62 KB
014. Other matrix derivatives.mp4 -
21.42 MB
014. Other matrix derivatives.srt -
8.57 KB
008.TensorFlow framework
015. What is TensorFlow.mp4 -
015. What is TensorFlow.mp4 -
39.44 MB
015. What is TensorFlow.srt -
14.67 KB
016. Our first model in TensorFlow.mp4 -
36.8 MB
016. Our first model in TensorFlow.srt -
13.84 KB
009.Philosophy of deep learning
017. What Deep Learning is and is not.mp4 -
017. What Deep Learning is and is not.mp4 -
29.46 MB
017. What Deep Learning is and is not.srt -
13.9 KB
018. Deep learning as a language.mp4 -
24.6 MB
018. Deep learning as a language.srt -
11.89 KB
010.Introduction to CNN
019. Motivation for convolutional layers.mp4 -
019. Motivation for convolutional layers.mp4 -
41.38 MB
019. Motivation for convolutional layers.srt -
15.97 KB
020. Our first CNN architecture.mp4 -
42.57 MB
020. Our first CNN architecture.srt -
13.32 KB
011.Modern CNNs
021. Training tips and tricks for deep CNNs.mp4 -
021. Training tips and tricks for deep CNNs.mp4 -
57.9 MB
021. Training tips and tricks for deep CNNs.srt -
18.18 KB
022. Overview of modern CNN architectures.mp4 -
32.24 MB
022. Overview of modern CNN architectures.srt -
9.52 KB
012.Applications of CNNs
023. Learning new tasks with pre-trained CNNs.mp4 -
023. Learning new tasks with pre-trained CNNs.mp4 -
19.28 MB
023. Learning new tasks with pre-trained CNNs.srt -
6.84 KB
024. A glimpse of other Computer Vision tasks.mp4 -
30.74 MB
024. A glimpse of other Computer Vision tasks.srt -
10.79 KB
013.Intro to Unsupervised Learning
025. Unsupervised learning what it is and why bother.mp4 -
025. Unsupervised learning what it is and why bother.mp4 -
23.78 MB
025. Unsupervised learning what it is and why bother.srt -
9.54 KB
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