I hereby claim:
- I am 0bserver07 on github.
- I am yad (https://keybase.io/yad) on keybase.
- I have a public key whose fingerprint is C9E6 2E90 35FB 2FBF DBEC DCD4 AF6B BAD6 11DB BFBF
To claim this, I am signing this object:
| # note replace PACKAGE_NAME | |
| import os | |
| import ast | |
| import json | |
| def parse_package(package_root): | |
| package_structure = {} | |
| for root, dirs, files in os.walk(package_root): | |
| relative_path = os.path.relpath(root, package_root) |
I hereby claim:
To claim this, I am signing this object:
| # Inspired by http://liuhongjiang.github.io/hexotech/2015/10/14/alembic-support-multiple-model-files/ | |
| def combine_metadata(): | |
| from sqlalchemy import MetaData | |
| import models # models file into which all models are imported | |
| model_classes = [] | |
| for model_name in models.__all__: | |
| model_classes.append(getattr(models, model_name)) |
| { "name":"component/adapters", "color":"bfd4f2"}, | |
| { "name":"component/config", "color":"bfd4f2"}, | |
| { "name":"component/documentation", "color":"bfd4f2"}, | |
| {"name":"component/extensions", "color":"bfd4f2"}, | |
| { "name":"component/handlers", "color":"bfd4f2"}, | |
| {"name":"component/http", "color":"bfd4f2"}, | |
| {"name":"component/language", "color":"bfd4f2"}, | |
| { "name":"component/logging", "color":"bfd4f2"}, | |
| { "name":"component/redis", "color":"bfd4f2"}, | |
| { "name":"component/robot", "color":"bfd4f2"}, |
"We extend the capabilities of neural networks by coupling them to external memory re- sources, which they can interact with by attentional processes."..."Preliminary results demon- strate that Neural Turing Machines can infer simple algorithms such as copying, sorting, and associative recall from input and output examples."
"Here we introduce a machine learning model called a differentiable neural computer (DNC), which consists of a neural network that can read from and write to an external memory matrix, analogous to the random-access memory in a conventional computer."..."Taken together, our results demonstrate that DNCs have the capacity to solve complex, structured tasks that are inaccessible to neural networks without external read–write memory."