Search Results for "python feature selection"
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Showing 12 open source projects for "python feature selection"
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Generative AI for Beginners (Version 3)
21 Lessons, Get Started Building with Generative AI
Generative AI for Beginners is a 21-lesson course by Microsoft Cloud Advocates that teaches the fundamentals of building generative AI applications in a practical, project-oriented way. Lessons are split into “Learn” modules for core concepts and “Build” modules with hands-on code in Python and TypeScript, so you can jump in at any point that matches your goals. The course covers everything from model selection, prompt engineering, and chat/text/image app patterns to secure development practices and UX for AI. It also walks through modern application techniques such as function calling, RAG with vector databases, working with open source models, agents, fine-tuning, and using SLMs. ... -
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VGGSfM
VGGSfM: Visual Geometry Grounded Deep Structure From Motion
VGGSfM is an advanced structure-from-motion (SfM) framework jointly developed by Meta AI Research (GenAI) and the University of Oxford’s Visual Geometry Group (VGG). It reconstructs 3D geometry, dense depth, and camera poses directly from unordered or sequential images and videos. The system combines learned feature matching and geometric optimization to generate high-quality camera calibrations, sparse/dense point clouds, and depth maps in standard COLMAP format. Version 2.0 adds support... -
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Kaldi
kaldi-asr/kaldi is the official location of the Kaldi project
Kaldi is an open source toolkit for speech recognition research. It provides a powerful framework for building state-of-the-art automatic speech recognition (ASR) systems, with support for deep neural networks, Gaussian mixture models, hidden Markov models, and other advanced techniques. The toolkit is widely used in both academia and industry due to its flexibility, extensibility, and strong community support. Kaldi is designed for researchers who need a highly customizable environment to... -
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Cactus
Low-latency AI inference engine optimized for mobile devices
Cactus is a low-latency, energy-efficient AI inference framework designed specifically for mobile devices and wearables, enabling advanced machine learning capabilities directly on-device. It provides a full-stack architecture composed of an inference engine, a computation graph system, and highly optimized hardware kernels tailored for ARM-based processors. Cactus emphasizes efficient memory usage through techniques such as zero-copy computation graphs and quantized model formats, allowing... -
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CogView
Text-to-Image generation. The repo for NeurIPS 2021 paper
CogView is a large-scale pretrained text-to-image transformer model, introduced in the NeurIPS 2021 paper CogView: Mastering Text-to-Image Generation via Transformers. With 4 billion parameters, it was one of the earliest transformer-based models to successfully generate high-quality images from natural language descriptions in Chinese, with partial support for English via translation. The model incorporates innovations such as PB-relax and Sandwich-LN to enable stable training of very deep... -
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cnn-for-image-retrieval is a research-oriented project that demonstrates the use of convolutional neural networks (CNNs) for image retrieval tasks. The repository provides implementations of CNN-based methods to extract feature representations from images and use them for similarity-based retrieval. It focuses on applying deep learning techniques to improve upon traditional handcrafted descriptors by learning features directly from data. The code includes training and evaluation scripts that...
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EasyArch
Arch Linux Installer ISO
A simple yet full featured Archlinux installer ISO. Minimum system requirements- Processor - 2 core 64 bit Ram - 1 GB HDD space - 10 GB If you are looking for another linux distro, then you are at wrong place, this is not a new or separate distribution. It is just a live ISO to provide simple and easy way to get Archlinux up and running in very little time and with or without internet connection. Yes, you read it right, you can install Archlinux without internet with this ISO.... -
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aioulinux
Linux for Arduino and Makers developers
Hello, I'm the Aioulinux founder, eager to professionally revive the project. Since 2018, the demand for an IoT and Arduino-tailored environment has been evident. Seeking partners for a 2024 version targeting schools and IoT companies, aiming for a secure and comprehensive platform. If you share this vision and wish to collaborate, reach out. Let's revive Aioulinux stronger than ever! Now seeking partners: Live Distro Specialist: Expert in live distributions to ensure... -
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asif
Arch-Linux Simple Install Framework
A simple cursor-based step by step install program enveloping the basic Archlinux installation process. It is used with Archlinux installation ISO image, in x86_64 live system only. The asif-pkg.tar shipping with packages does not require a network connection. The asif.tar needs a network connection, and please remember to configure your /etc/pacman.d/mirrorlist. f2fs and MVNe support is added. I will update the UI to make it selectable later. Sorry I got no spare time for... -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Randirplay
Generates a playlist of files in directories in random directory order
...lots of directory scanning configuration options and size limiting. Will also produce a playlist to fit the free space on a specified device. Good for grabbing a random selection of albums to transfer to your device or just to be able to play albums in a random order if your device doesn't have this feature. You can also use it to generate separate playlists for separate directories by running it multiple times in another script (this is my current use for it in my Android device). -
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Tools to build molecular-docking activity prediction models by PLS regression with iterative training and pose-selection. Descriptors include (i) docking score(s), (ii) pharmacophore features, (iii) multi-feature descriptors learned by decision trees.
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The Job Jar is a simple batch queuing system for Unix. Its main distinguishing feature is that there is no central daemon. Instead, an arbitrary set of workers cooperatively claim jobs from a central directory. A job is any Unix executable file.
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