fchollet

10 ms·

91.
by fchollet 10y ago
If anyone wants to switch to TensorFlow but misses the Torch interface, you will always have Keras: https://github.com/fchollet/keras
92.
by fchollet 10y ago
> If SF's city officials can pull it off, with the increased investments in public transportation eventually San Francisco is going to become a global A+ city. This is the most hilarious comment I've read on HN in a long time.
93.
by fchollet 10y ago
The functional API removes the need for a dedicated autoencoder layer. But maybe in the future we will have a dedicated autoencoder model , if there's interest in that (with autoencoder-specific methods).
94.
by fchollet 10y ago
Layers have always had an activation argument, this is not new. And yes, there is still an Activation layer. You can specify an activation function via either option.
95.
by fchollet 10y ago
Yes, I think we should work on a FAQ to introduce common ML concepts and their implementation in Keras. Any specific concept that you had trouble with?
96.
by fchollet 10y ago
A few advantages: - it's much easier to use. Using pure TensorFlow is considered "advanced" and requires familiarity with deep learning, understanding of what a symbolic computation graph is, etc. Keras, meanwhile, is meant t
97.
Keras 1.0 – Python deep learning framework(blog.keras.io)
180 points by fchollet 10y ago|17 comments
98.
Deep learning for visual question answering: demo with Keras code(iamaaditya.github.io)
73 points by fchollet 11y ago|17 comments
99.
by fchollet 11y ago
I agree that sklearn-compatibility is the strong point of Skflow. If you are familiar with Keras, note that you can do the same with any Keras model, via the sklearn wrapper: https://github.com/fchollet/keras/blob&
100.
Open-source implementation of AlphaGo in Keras(github.com)
7 points by fchollet 11y ago|1 comments
101.
by fchollet 11y ago
It's really neat stuff. The 3rd example is especially stunning. For more projects like this, you can also check out the neural style transfer implementation in Keras: https://github.com/fchollet/keras/blob&#x2
102.
Deep Learning for Visual Question Answering(kdnuggets.com)
1 points by fchollet 11y ago|0 comments
103.
by fchollet 11y ago
So Periscope and Moments would be the saving grace of Twitter? On what planet does the author live?
104.
by fchollet 11y ago
It's served from Microsoft Bob Server ®
105.
Keras, now running on TensorFlow(blog.keras.io)
7 points by fchollet 11y ago|0 comments
106.
by fchollet 11y ago
> Is it common practice to use the most frequent words as features ? It looks like they don't carry much information, by definition. The common practice with a small-ish dataset is to use e.g. the top 10k or 20k most frequent words,
107.
Keras: an introduction [pdf](uwaterloo.ca)
2 points by fchollet 11y ago|0 comments
108.
by fchollet 11y ago
Confusing, still pretty buggy. Maybe it's a bit early to release? I'll try to compile some constructive feedback in a bit.
109.
Deep Learning for Visual Question Answering(github.com)
3 points by fchollet 11y ago|0 comments
110.
Teaching Recurrent Neural Networks about Monet(blog.manugarri.com)
1 points by fchollet 11y ago|0 comments
111.
by fchollet 11y ago
These two things are non-trivial, but not particularly hard in themselves. However, doing them at ultra-low latency becomes quite a challenge. Doing anything at ultra-low latency is already a challenge, but especially so when what you&#x2
112.
by fchollet 11y ago
Excellent news. Hopefully with this release we will be able to lift the remaining limitations of the TensorFlow version of Keras (tensor contraction, float<->bool casting, and RNNs over sequences with arbitrary length). https:/&
113.
Deep learning for crosswalk detection in aerial pictures(github.com)
2 points by fchollet 11y ago|0 comments
114.
Deep reinforcement learning with TensorFlow(github.com)
1 points by fchollet 11y ago|0 comments
115.
Keras, now running on TensorFlow(github.com)
21 points by fchollet 11y ago|3 comments
116.
by fchollet 11y ago
> Maybe they should make a law or something that 1 out of every 100 news must be fake In the world I live in, the proportion is far higher. Especially if you are talking about the mainstream media. Hell, easily one of 100 peer-reviewed
117.
by fchollet 11y ago
While it would be much more energy-efficient, such a process is bound to have a very low rate of weeds destroyed / minute.
118.
by fchollet 11y ago
Here's the MS COCO leaderboard: http://mscoco.org/dataset/#captions-leaderboard Google's Show and Tell seems considerably superior to competing approaches.
119.
by fchollet 11y ago
I suspect this would result in rather superficial weed destruction, since the roots underground would be unharmed and would cause the weed to regrow a few days later. Unrooting the weeds definitely sounds more reliable to me.
120.
by fchollet 11y ago
Let the laws of physics do the recurrent math for you. Analog RNN computers would be very interesting, but they would first setting in stone the basics of the algorithms we use. We are still only beginning to explore the algorithm space, an

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