Best Deep Learning podcasts we could find (Updated June 2019)
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Find me on Github/Twitter/Kaggle @SamDeepLearning.Find me on LinkedIn @SamPutnam. This Podcast is supported by Enterprise Deep Learning | Cambridge/Boston | New York City | Hanover, NH | http://www.EnterpriseDeepLearning.com. Contact: Sam@EDeepLearning.com, 802-299-1240, P.O. Box 863, Hanover, NH, USA, 03755. We move deep learning to production. I teach the worldwide Deploying Deep Learning Masterclass at http://www.DeepLearningConf.com in NYC regularly and am a Deep Learning Consultant serv ...
 
Deep Learning (DL) has attracted much interest in a wide range of applications such as image recognition, speech recognition and artificial intelligence, both from academia and industry. This lecture introduces the core elements of neural networks and deep learning, it comprises: (multilayer) perceptron, backpropagation, fully connected neural networks loss functions and optimization strategies convolutional neural networks (CNNs) activation functions regularization strategies common practic ...
 
ClusterOne is the deep learning platform for TensorFlow and many other AI frameworks. If you want to flexibly manage your projects then this is the right platform for your needs. Get additional detail by visiting at: https://clusterone.com/
 
If you need large scale deep learning platform then ClusterOne is one of the powerful solutions will exceed your expectations. It is flexible platform with intuitive interfaces so can be great help for you. For additional detail, visit: https://clusterone.com/
 
If you need help with deep learning then a powerful deep learning platform can be great help. And for your distinct needs, ClusterOne is the most flexible and powerful deep learning platform will definitely exceed your expectations. For more detail, visit at: https://clusterone.com/about/
 
Deep Learning (DL) has attracted much interest in a wide range of applications such as image recognition, speech recognition and artificial intelligence, both from academia and industry. This lecture introduces the core elements of neural networks and deep learning, it comprises: (multilayer) perceptron, backpropagation, fully connected neural networks loss functions and optimization strategies convolutional neural networks (CNNs) activation functions regularization strategies common practic ...
 
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If you need help with deep learning then a powerful deeplearning platform can be great help And for your distinct needs ClusterOne isthe most flexible and powerful deep learning platform will definitely exceedyour expectations For more detail visit at httpsclusteronecomaboutBy Robert Keller.
 
ClusterOne is the deep learning platform for TensorFlow andmany other AI frameworks If you want to flexibly manage your projects thenthis is the right platform for your needs Get additional detail by visitingat httpsclusteronecomBy Robert Keller.
 
If you need large scale deep learning platform then ClusterOne is one of the powerful solutions will exceed your expectations. It is flexible platform with intuitive interfaces so can be great help for you. For additional detail, visit: https://clusterone.com/By Robert Keller.
 
Justin Johnson, now at Facebook, wrote the original Torch implementation of the Gatys 2015 paper, which combines the content of one image and the style of another image using convolutional neural networks. Manuel Ruder’s newer 2016 paper transfers the style of one image to a whole video sequence, and it uses a computer vision technique called o ...…
 
I talk through generating 10 melodies, two of which I play at the conclusion using a model trained on thousands of midi examples contained in a .mag Magenta file bundle. I used the Biaxial RNN (https://github.com/hexahedria/biaxial-rnn-music-composition) by a student named Daniel Johnson and the Basic RNN (https://github.com/tensorflow/magenta/ ...…
 
I talk through generating an image of IRS tax return characters using a model trained on the IRS tax return dataset - NMIST. The authors trained for 70 hours on 32 GPUs. I used unconditioned image generation to create an image in 6 hours on my MacBook Pro CPU. I used the TensorFlow implementation of Conditional Image Generation with PixelCNN De ...…
 
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