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Artificial Intelligence
The branch of computer science dealing with the reproduction, or mimicking of human-level intelligence, self-awareness, knowledge, conscience, and thought in computer programs.
Here are 7,634 public repositories matching this topic...
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Currently, when entering epic mode the README is frozen in the last level of the tower. When you're trying to fine-tune the score for a level other than the last one, it would be helpful if we had the README for that level available. The proposal is that when entering epic mode, the README is updated with all levels, one following the other.
Example:
# Starbolt - beginner-
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MLflow seems to have a length limit of 5000 when setting tags (see below).
[...]
File "/home/smay/miniconda3/envs/py38/lib/python3.8/site-packages/mlflow/utils/validation.py", line 136, in _validate_length_limit
raise MlflowException(
mlflow.exceptions.MlflowException: Tag value '[0.8562690322984875, 0.8544098885636596, 0.8544098885636596, 0.8544098885636596, 0.85440988856365-
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Oct 14, 2020 - Shell
Support @ as HEAD
Git supports the usage of the at symbol @ and it is equivalent to HEAD (more details).
If I am not mistaken, dvc does not support it. At least the following command fails for dvc==1.8.4:
dvc metrics diff master @
ERROR: failed to show metrics diff - unkn
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/tmp/ has been hard coded in some instances
This will be replaced with https://docs.python.org/3/library/tempfile.html which has been well implemented in some instances in the code.
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2019/12/02 和Yi Wang沟通交流考虑SQLFLOW可以支持如下的特性
一、基础功能:好用的工具需要一个更加简易友好的界面,让业务开发/分析更加简单
1)设计分析类工具,提供自动联想输入、快速语法、常见语义错误,提升用户体验
应用场景:提供IDE的自动联想功能,提高开发效率;语法和基本语义提前检查,避免提交到后台,执行较长时间后报错
2)大数据量时时间较长,建议提供任务(job)管理、允许用户了解数据执行的状态、监控进度、提供动态调试、watch能力,方便用户感知和调优
应用场景:耗时任务可以快速了解整体进度,提供一些中间的过程信息、耗时等,方便用户进行调优,优化开发
3) 安全权限、用户管理、
应用场景:增加新的数据分析人员、用户权
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PrestoDB https://prestodb.io .. is widely used as SQL frontend for many different data-sources, including ElasticSearch, and even files in S3 .. would be very nice if there would be a Connector available for Vespa.
Interpret
Yes


Add a mapping between custom accelerators and "nicknames" so that you can
Trainer(accelerator=‘nickname’)