Deep Learning, NLP, NMT, AI, ML
Country-specific serializers fields, to Django Rest Framework Documentation (soon) The full documentation is at https://django-rest-localflavor.readthedocs.org. Quickstart Install django-rest-localflavor: pip install django-rest-localflavor Then use it in a project: INSTALLED_APPS = ( # … ‘rest_framework’, ‘rest_localflavor’, ) GitHub https://github.com/gilsondev/django-rest-localflavor
Read more
Overview JSON:API support for Django REST framework By default, Django REST framework will produce a response like: { “count”: 20, “next”: “http://example.com/api/1.0/identities/?page=3”, “previous”: “http://example.com/api/1.0/identities/?page=1”, “results”: [{ “id”: 3, “username”: “john”, “full_name”: “John Coltrane” }] } However, for an identity model in JSON:API format the response should look like the following: { “links”: { “prev”: “http://example.com/api/1.0/identities”, “self”: “http://example.com/api/1.0/identities?page=2”, “next”: “http://example.com/api/1.0/identities?page=3”, }, “data”: [{ “type”: “identities”, “id”: “3”, “attributes”: { “username”: “john”, “full-name”: “John Coltrane” } }], “meta”: { “pagination”: { “count”: […]
Read more
TensorFlow Fold is a library for creating TensorFlow models that consume structured data, where the structure of the computation graph depends on the structure of the input data. For example, this model implements TreeLSTMs for sentiment analysis on parse trees of arbitrary shape/size/depth. Fold implements dynamic batching. Batches of arbitrarily shaped computation graphs are transformed to produce a static computation graph. This graph has the same structure regardless of what input it receives, and can be executed efficiently by TensorFlow. […]
Read more
Deploy tensorflow graphs for fast evaluation and export to tensorflow-less environments running numpy. Now with tensorflow 1.0 support. Evaluation usage import tfdeploy as td import numpy as np model = td.Model(“/path/to/model.pkl”) inp, outp = model.get(“input”, “output”) batch = np.random.rand(10000, 784) result = outp.eval({inp: batch}) Installation and dependencies
Read more
Convolutional Neural Networks Are Beautiful We all take our eyes for granted, we glance at an object for an instant and our brains can identify with ease. However distorted the information may be, we do a pretty good job at it. Low light, obscured vision, poor eyesight… There are a myriad of situations where conditions are poor but still we manage to understand what an object is. Context helps, but we humans were created with sight in mind. Computers have […]
Read more
A web application which stands as a toolkit for climate change law assessment. Prerequisites Installing the application Get the source code: git clone https://github.com/eaudeweb/lcc-toolkit cd lcc-toolkit Customize the environment files: cp docker/postgres.env.example docker/postgres.env cp docker/web.env.example docker/web.env cp docker/init.sql.example docker/init.sql Depending on the installation mode, create the docker-compose.override.yml file: cp docker-compose.override.[prod|dev].yml docker-compose.override.yml Start the application stack: docker-compose up -d docker-compose logs Attach to the web service: docker-compose run web Create a superuser (for Ansible see https://gist.github.com/elleryq/9c70e08b1b2cecc636d6) python manage.py createsuperuser That’s it. […]
Read more
sphinxcontrib-needs Sphinx-Needs allows the definition, linking and filtering of class-like need-objects, which are by default: requirements specifications implementations test cases. This list can be easily customized via configuration (for instance to support bugs or user stories). A default requirement need looks like: Layout and style of needs can be highly customized, so that a need can also look like: Take a look into our Examples for more pictures and ideas how to use Sphinx-Needs. For filtering and analyzing needs, Sphinx-Needs […]
Read more
A simple yet powerful wrapper for the YouTube Analytics API. Features Pythonic syntax lets you feel right at home Dynamic error handling saves hours of troubleshooting, and makes sure only valid requests count toward your API quota A clever interface allows you to make multiple requests across multiple sessions without reauthorising Extra support allows the native saving of CSV files and conversion to DataFrame objects Easy enough for beginners, but powerful enough for advanced users Installation You need Python 3.6.0 […]
Read more
pubmex.py is a script to get a fancy paper title based on given DOI or PMID (can be also combined with macOS Finder) Format of the title: a first author . a last author – (title(“dotted”) or your customed title) . PMID . journal . year . pdf e.g. Kelley.Scott.The.evolution.biology.shift.towards.engineering.prediction-generating.tools.away.traditional.research.practice.EMBORep.2008.pdf Nowadays, it’s not a big issue, with all Mendeley and other tools, however… I don’t want to put any PDF file collected on the way into my library, because then […]
Read more
Enables Unreal Engine-style Right Mouse Viewport Navigation. This addon maps Blender’s Walk/Fly Navigation to the Right Mouse Button, while retaining context menu functionality across all 3D Viewport modes for the same button. How to Install Download RightMouseNavigation.zip from the Releases section on the right, then install by opening Blender, selecting Edit > Preferences > Addons > Install then select RightMouseNavigation.zip and click Install Addon How to Use Right Mouse Hold + WASD to Navigate 3D Viewport Right Mouse Click to […]
Read more