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[FreeCoursesOnline.Me] Coursera - Introduction to Deep Learning
Category:
Other
Size:
1.27 GB
Seeders:
2
Leechers:
2
Downloads:
385
Uploaded:
Oct 21, 2018
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[FreeCoursesOnline.Me] Coursera - Introduction to Deep Learning
001.Specialization Promo
001. Welcome to AML specialization!.mp4
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001. Welcome to AML specialization!.srt
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002.Course intro
002. Course intro.mp4
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002. Course intro.srt
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003.Linear model as the simplest neural network
003. Linear regression.mp4
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003. Linear regression.srt
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004. Linear classification.mp4
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004. Linear classification.srt
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005. Gradient descent.mp4
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005. Gradient descent.srt
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004.Regularization in machine learning
006. Overfitting problem and model validation.mp4
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006. Overfitting problem and model validation.srt
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007. Model regularization.mp4
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007. Model regularization.srt
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005.Stochastic methods for optimization
008. Stochastic gradient descent.mp4
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008. Stochastic gradient descent.srt
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009. Gradient descent extensions.mp4
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009. Gradient descent extensions.srt
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006.The simplest neural network MLP
010. Multilayer perceptron (MLP).mp4
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010. Multilayer perceptron (MLP).srt
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011. Chain rule.mp4
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011. Chain rule.srt
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012. Backpropagation.mp4
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012. Backpropagation.srt
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007.Matrix derivatives
013. Efficient MLP implementation.mp4
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013. Efficient MLP implementation.srt
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014. Other matrix derivatives.mp4
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014. Other matrix derivatives.srt
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008.TensorFlow framework
015. What is TensorFlow.mp4
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015. What is TensorFlow.srt
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016. Our first model in TensorFlow.mp4
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016. Our first model in TensorFlow.srt
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009.Philosophy of deep learning
017. What Deep Learning is and is not.mp4
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017. What Deep Learning is and is not.srt
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018. Deep learning as a language.mp4
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018. Deep learning as a language.srt
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010.Introduction to CNN
019. Motivation for convolutional layers.mp4
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019. Motivation for convolutional layers.srt
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020. Our first CNN architecture.mp4
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020. Our first CNN architecture.srt
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011.Modern CNNs
021. Training tips and tricks for deep CNNs.mp4
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021. Training tips and tricks for deep CNNs.srt
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022. Overview of modern CNN architectures.mp4
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022. Overview of modern CNN architectures.srt
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012.Applications of CNNs
023. Learning new tasks with pre-trained CNNs.mp4
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023. Learning new tasks with pre-trained CNNs.srt
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024. A glimpse of other Computer Vision tasks.mp4
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024. A glimpse of other Computer Vision tasks.srt
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013.Intro to Unsupervised Learning
025. Unsupervised learning what it is and why bother.mp4
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025. Unsupervised learning what it is and why bother.srt
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026. Autoencoders 101.mp4
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026. Autoencoders 101.srt
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014.More Autoencoders
027. Autoencoder applications.mp4
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027. Autoencoder applications.srt
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028. Autoencoder applications image generation, data visualization & more.mp4
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028. Autoencoder applications image generation, data visualization & more.srt
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015.Word Embeddings
029. Natural language processing primer.mp4
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029. Natural language processing primer.srt
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030. Word embeddings.mp4
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030. Word embeddings.srt
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016.Generative Adversarial Networks
031. Generative models 101.mp4
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031. Generative models 101.srt
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032. Generative Adversarial Networks.mp4
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032. Generative Adversarial Networks.srt
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033. Applications of adversarial approach.mp4
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033. Applications of adversarial approach.srt
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017.Introduction to RNN
034. Motivation for recurrent layers.mp4
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034. Motivation for recurrent layers.srt
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035. Simple RNN and Backpropagation.mp4
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035. Simple RNN and Backpropagation.srt
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018.Modern RNNs
036. The training of RNNs is not that easy.mp4
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036. The training of RNNs is not that easy.srt
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037. Dealing with vanishing and exploding gradients.mp4
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037. Dealing with vanishing and exploding gradients.srt
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038. Modern RNNs LSTM and GRU.mp4
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038. Modern RNNs LSTM and GRU.srt
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019.Applications of RNNs
039. Practical use cases for RNNs.mp4
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039. Practical use cases for RNNs.srt
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[FreeCoursesOnline.Me].url
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[FreeTutorials.Us].url
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[FTU Forum].url
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InfoHash:
EF0143A5DC7492F78FDD45DA06A02B70071DFDB3
Last updated:
Jan 24, 2022
File count:
81 B
File Category:
1
Tags:
freecoursesonline, coursera, introduction, deep, learning
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