URL(s) with the issue:

https://github.com/ManishAradwad/examples/blob/9f7d80aff8214b358e4aea0b83f2648748990c4b/courses/udacity_intro_to_tensorflow_for_deep_learning/l07c01_saving_and_loading_models.ipynb#L579

The differnece in output should be zero:

Description of issue (what needs changing):

differnece should be difference

Submit a pull request?

Yes

As indicated in the FAQ, the way to import ResNeXt101 is from keras.applications.resnext import ResNeXt101. But in the latest Keras 2.3.1 and Keras-Applications 1.0.8, it gives ImportError: No module named 'keras.applications.resnext'. I try to change it to `from keras_applications.resnext import preproces

In this article https://link.springer.com/article/10.1186/1471-2105-8-25 concerns about using gini for feature importance is being raised.

We found that for the original random forest method the variable importance measures are affected by the number of categories and scale of measurement of the predictor variables, which are no direct indicators of the true importance of the variable.

https://github.com/aymericdamien/TensorFlow-Examples/blob/9e1bb504f5d0f209d000997ce2ad95bb891798ab/examples/3_NeuralNetworks/bidirectional_rnn.py#L81

I think "outputs [-1]" and "outputs [0]" are equivalent (reversed) in this line of code, but the former (89%) works better than the latter (86%). Why?

Context

We would like to add torch::nn::functional::normalize to the C++ API, so that C++ users can easily find the equivalent of Python API torch.nn.functional.normalize.

Steps

• Add torch::nn::NormalizeOptions to torch/csrc/api/include/torch/nn/options/normalization.h (add this file if it doesn’t exist), which should include the following parameters (based on https://pytorch.

Short description

I am trying to train Tesseract on Akkadian language. The language-specific.sh script was modified accordingly. When converting the training text to TIFF images, the text2image program crashes.

Environment

• Tesseract Version: 3.04.01
• Commit Number: the standard package in Ubuntu, package version 3.04.01-4, commit unknown
• Platform: Linux ubuntu

• face_recognition version: 1.2.3
• Python version: 3.7
• Operating System: Debian 10.1

Description

face_detection need to scan "known_people" directory every time.
in "known_people" directory I've 20 people and face_detection need a lot of time to "learn" before search known peoples inside new photos (unknown_pictures directory contain 2 photos).
it's possible to cache "learn" anali

Could someone tell me if this example comes with any documents about preparing data, training, and testing? Thanks.

As reported on discourse, the REPL help doesn't show tab completion info for emoji even when it exists, unlike for other Unicode completions:

help?> α
"α" can be typed by \alpha<tab>
search:

Couldn't find α
Perhaps you meant !, %, &, *, +, -, /, :, <, >, \, ^, |, ~, 

This should really help to keep a track of papers read so far. I would love to fork the repo and keep on checking the boxes in my local fork.

For example: Have a look at this section. People fork this repo and check the boxes as they finish reading each section.

https://xgboost.readthedocs.io/en/latest/python/python_api.html#module-xgboost.sklearn

Doesn't specify if monotone constraints are usable (it seems like they are but i'm not entirely sure since it doesn't explicitly specify.

Thanks in advance

EDIT: neither does it appear here:

https://github.com/dmlc/xgboost/blob/master/doc/parameter.rst

Alexnet implementation in tensorflow has incomplete architecture where 2 convolution neural layers are missing. This issue is in reference to the python notebook mentioned below.

https://github.com/donnemartin/data-science-ipython-notebooks/blob/master/deep-learning/tensor-flow-examples/notebooks/3_neural_networks/alexnet.ipynb

What's the ETA for updating the massively outdated documentation?

Please update all documents that are related building CNTK from source with latest CUDA dependencies that are indicated in CNTK.Common.props and CNTK.Cpp.props.
I tried to build from source, but it's a futile effort.

I am having difficulty in running this package as a Webservice. Would appreciate if we could provide any kind of documentation on implementing an API to get the keypoints from an image. Our aim is to able to deploy this API as an Azure Function and also know if it is feasible.

I was going though the existing enhancement issues again and though it'd be nice to collect ideas for spaCy plugins and related projects. There are always people in the community who are looking for new things to build, so here's some inspiration ✨ For existing plugins and projects, check out the spaCy universe.

If you have questions about the projects I suggested,

I recently added "back to top" button to README. What other features would make it easier to browse? Please write your recommendation.

Thanks for maintaining this awesome list. I'd like to suggest to add a release when a change is made to the README file. With this, we can watch the project without getting lots of activity emails.