Oxford-Deep Learning
视频
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2017-8-22 03:16
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2024-12-21 05:38
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130
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4.98 GB
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16
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- Lectures/Deep Learning Lecture 1- Introduction.mp4366.33MB
- Lectures/Deep Learning Lecture 10- Convolutional Neural Networks.mp4304.21MB
- Lectures/Deep Learning Lecture 11- Max-margin learning, transfer and memory networks.mp4368.22MB
- Lectures/Deep Learning Lecture 12- Recurrent Neural Nets and LSTMs.mp4318.09MB
- Lectures/Deep Learning Lecture 13- Alex Graves on Hallucination with RNNs.mp4321.88MB
- Lectures/Deep Learning Lecture 14- Karol Gregor on Variational Autoencoders and Image Generation.mp4263.39MB
- Lectures/Deep Learning Lecture 15- Deep Reinforcement Learning - Policy search.mp4334.74MB
- Lectures/Deep Learning Lecture 16- Reinforcement learning and neuro-dynamic programming.mp4336.36MB
- Lectures/Deep Learning Lecture 2- linear models.mp4277.68MB
- Lectures/Deep Learning Lecture 3- Maximum likelihood and information.mp4416.35MB
- Lectures/Deep Learning Lecture 4- Regularization, model complexity and data complexity (part 1).mp4248.2MB
- Lectures/Deep Learning Lecture 5- Regularization, model complexity and data complexity (part 2).mp4361.11MB
- Lectures/Deep Learning Lecture 6- Optimization.mp4328.43MB
- Lectures/Deep learning Lecture 7- Logistic regression, a Torch approach.mp4250.5MB
- Lectures/Deep Learning Lecture 8- Modular back-propagation, logistic regression and Torch.mp4285.79MB
- Lectures/Deep Learning Lecture 9- Neural networks and modular design in Torch.mp4317.19MB
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