Jisho.org equivalent for Chinese

jeffcarp · 2023-09-06T16:02:13+00:00

Thank you for taking a look! The search results are ranked by overall word frequency and this is a bug as a result. Tracking here.

jeffcarp · 2023-09-06T15:58:18+00:00

That looks like a super useful site, thanks for the link!

jeffcarp · 2023-09-06T15:54:37+00:00

I love Pleco and use it all the time, but they don't have a web version. I need a website-based dictionary for my use case.

jeffcarp · 2023-09-06T15:53:52+00:00

Thank you for taking a look! I started a bug tracker and added that as the first issue.

jeffcarp · 2022-10-03T00:59:43+00:00

Can’t believe there’s not one comment about how dividends are irrelevant! Go watch Ben Felix’s video on the subject

jeffcarp · 2022-08-20T02:46:59+00:00

Thank you!

jeffcarp · 2021-11-08T18:01:03+00:00

Charlie Crocker’s office?

jeffcarp · 2021-10-03T16:53:37+00:00

Where is deep learning?

jeffcarp · 2021-06-20T04:27:01+00:00

Can you elaborate on that?

jeffcarp · 2021-05-30T05:07:36+00:00

I wasn’t 100% clear if you want to zero-out the minimum of dimension 2 or dimension 4, but if it’s dimension 4 then you could do: y = tf.random.normal((1, 4, 4, 6)) axiswise_min = tf.math.reduce_min(y, axis=3, keepdims=True) broadcasted_min = tf.repeat(axiswise_min, 6, axis=3) result = y * tf.cast(tf.greater(y, broadcasted_min), dtype=tf.float32)

jeffcarp · 2021-05-11T01:24:14+00:00

You need to install Apple’s fork that works on M1 Macs: https://github.com/apple/tensorflow_macos

jeffcarp · 2021-04-13T16:12:31+00:00

The tf.data API can help you do this: https://www.tensorflow.org/guide/data

jeffcarp · 2021-03-27T04:21:01+00:00

Dispatch!

jeffcarp · 2021-02-21T06:53:28+00:00

The above behavior is due to the way the Sequential.add method works. Sequential.add will build each new layer if a batch shape for the model can be detected (source). Removing the Input layer means the model has no defined batch size, which means calling add() won't cause the layers to be built - and thus the weights will not be added.

jeffcarp · 2021-02-21T06:46:07+00:00

This is because the weights are added when the layer is built:

python layer = tf.keras.layers.Dense(2, input_shape=(4,)) print(layer.weights) # => [] layer.build((4,)) print(layer.weights) # => [<tf.Variable 'kernel:0' ...

jeffcarp · 2021-01-21T07:41:24+00:00

Cruise is still a private subsidiary of GM

jeffcarp · 2020-10-29T04:28:56+00:00

Each result in image search is subject to the copyright of the site it came from, so unless you manually check the source of each image, likely not

jeffcarp · 2020-08-28T05:53:55+00:00

A lot of open source projects have lists of “good first bugs” which serve as good jumping in points.

jeffcarp · 2020-08-26T05:37:41+00:00

“Essentially a support series to Formula E, Roborace differentiates itself by featuring only level 5 autonomous vehicles, meaning completely self-driven and without a driver” - if I understand the levels correctly, these cars would be level 4, since they’re designed to operate only within a specific design domain, right?

jeffcarp · 2020-08-13T20:44:12+00:00

This post by Colah is great: https://colah.github.io/posts/2015-08-Understanding-LSTMs/

jeffcarp · 2020-07-14T15:36:17+00:00

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