Search Results for "compiler python linux" - Page 3
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Showing 58 open source projects for "compiler python linux"
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The most trusted software in constructionHCSS provides easy-to-use software built for construction companies that want to win more work, work smarter, and boost profits. For nearly 40 years, we've helped heavy civil contractors, infrastructure builders, and utility companies improve operations, from estimating and project management to field tracking, equipment maintenance, and safety. Tools like HeavyBid, HeavyJob, and HCSS Safety are built for the field and designed to work together, giving your team real-time visibility, tighter cost control, and better job outcomes. With 45+ accounting integrations and customizable APIs, HCSS fits seamlessly into your tech stack. We regularly update our software based on feedback from real crews, ensuring it fits the way your team works. Backed by award-winning 24/7/365 support and a proven implementation process, HCSS helps reduce risk, cut inefficiencies, and deliver fast ROI. If you're ready to grow your business and gain a competitive edge, HCSS is the partner that gets you there.
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Rainbow
Rainbow: Combining Improvements in Deep Reinforcement Learning
Combining improvements in deep reinforcement learning. Results and pretrained models can be found in the releases. Data-efficient Rainbow can be run using several options (note that the "unbounded" memory is implemented here in practice by manually setting the memory capacity to be the same as the maximum number of timesteps). -
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Easy-TensorFlow
Simple and comprehensive tutorials in TensorFlow
The goal of this repository is to provide comprehensive tutorials for TensorFlow while maintaining the simplicity of the code. Each tutorial includes a detailed explanation (written in .ipynb) format, as well as the source code (in .py format). There is a necessity to address the motivations for this project. TensorFlow is one of the deep learning frameworks available with the largest community. This repository is dedicated to suggesting a simple path to learn TensorFlow. In addition to the... -
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Deep Reinforcement Learning for Keras
Deep Reinforcement Learning for Keras.
keras-rl implements some state-of-the-art deep reinforcement learning algorithms in Python and seamlessly integrates with the deep learning library Keras. Furthermore, keras-rl works with OpenAI Gym out of the box. This means that evaluating and playing around with different algorithms is easy. Of course, you can extend keras-rl according to your own needs. You can use built-in Keras callbacks and metrics or define your own. Even more so, it is easy to implement your own environments and... -
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Intel neon
Intel® Nervana™ reference deep learning framework
neon is Intel's reference deep learning framework committed to best performance on all hardware. Designed for ease of use and extensibility. See the new features in our latest release. We want to highlight that neon v2.0.0+ has been optimized for much better performance on CPUs by enabling Intel Math Kernel Library (MKL). The DNN (Deep Neural Networks) component of MKL that is used by neon is provided free of charge and downloaded automatically as part of the neon installation. The gpu... -
Eurekos LMS - Build a Smarter CustomerEurekos is a purpose-built LMS that engages customers throughout the entire learning journey from pre-sales, to onboarding, and everything after.
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WikiSQL
A large annotated semantic parsing corpus for developing NL interfaces
A large crowd-sourced dataset for developing natural language interfaces for relational databases. WikiSQL is the dataset released along with our work Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning. Regarding tokenization and Stanza, when WikiSQL was written 3-years ago, it relied on Stanza, a CoreNLP python wrapper that has since been deprecated. If you'd still like to use the tokenizer, please use the docker image. We do not anticipate switching... -
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This project provides a framework for testing and comparing different machine learning algorithms (particularly reinforcement learning methods) in different scenarios. Its intended area of application is in research and education.
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A Python class library of tools for learning agents, including reinforcement learning algorithms, function approximators, and vector quantizations algorithms. (Pronounced "plastic".)
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General purpose agents using reinforcement learning. Combines radial basis functions, temporal difference learning, planning, uncertainty estimations, and curiosity. Intended to be an out-of-the-box solution for roboticists and game developers.
