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Updated
Oct 2, 2021
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The branch of computer science dealing with the reproduction, or mimicking of human-level intelligence, self-awareness, knowledge, conscience, and thought in computer programs.
Visualizer for neural network, deep learning, and machine learning models
Learn OpenCV : C++ and Python Examples
Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research
This is an MLflow Roadmap item that has been prioritized by the MLflow maintainers. We're seeking help with the implementation of roadmap items tagged with the help wanted label.
For requirements clarifications and implementation questions, or to request a PR review, please tag @BenWilson2 in your communications related to this issue.
Includ
Mapping a variable-length sentence to a fixed-length vector using BERT model
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
Got error message on an empty directory, shouldn't it show nothing? like ls command.
 courses, books, video lectures and papers.
A curated list of references for MLOps
An open source library for deep learning end-to-end dialog systems and chatbots.
Mycroft Core, the Mycroft Artificial Intelligence platform.
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
A system for quickly generating training data with weak supervision
With a config like this
{
"METAFLOW_DATASTORE_SYSROOT_S3": "s3://mf-test/metaflow/",
}
(note a slash after METAFLOW_DATASTORE_SYSROOT_S3)
metaflow.S3(run=self).put* produces double-slashes like here:
s3://mf-test/metaflow//data/DataLoader/1630978962283843/month=01/data.parquet
The trailing slash in the config shouldn't make a difference
(⌐■_■) - Deep Reinforcement Learning instrumenting bettercap for WiFi pwning.
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
Proposed refactoring or deprecation
Update the imports in the Lightning Quantization callback to
torch.ao.quantizationMotivation
Quantization in PyTorch 1.10 is moving under the
torch.aomodule namespace:https://github.com/pytorch/pytorch/blob/3d6d4f4322e42886349b822449b9e439fac89ae2/torch/quantization/quant