Search Results for "fast linux" - Page 8
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Showing 211 open source projects for "fast linux"
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Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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DrQA
Reading Wikipedia to Answer Open-Domain Questions
DrQA is an open-domain question answering system that reads large text corpora—famously Wikipedia—to answer natural language questions with extractive spans. It follows a two-stage pipeline: a fast document retriever first narrows down candidate articles, and a neural machine reader then predicts the exact answer span from those passages. The retriever relies on classic IR features (like TF-IDF and n-gram statistics) to remain lightweight and scalable to millions of documents. The reader is... -
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Gluon CV Toolkit
Gluon CV Toolkit
GluonCV provides implementations of state-of-the-art (SOTA) deep learning algorithms in computer vision. It aims to help engineers, researchers, and students quickly prototype products, validate new ideas and learn computer vision. It features training scripts that reproduce SOTA results reported in latest papers, a large set of pre-trained models, carefully designed APIs and easy-to-understand implementations and community support. From fundamental image classification, object detection,... -
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BudgetML
Deploy a ML inference service on a budget in 10 lines of code
Deploy a ML inference service on a budget in less than 10 lines of code. BudgetML is perfect for practitioners who would like to quickly deploy their models to an endpoint, but not waste a lot of time, money, and effort trying to figure out how to do this end-to-end. We built BudgetML because it's hard to find a simple way to get a model in production fast and cheaply. Deploying from scratch involves learning too many different concepts like SSL certificate generation, Docker, REST,... -
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Tabnine
Vim client for TabNine
Tabnine is an AI-powered code completion extension trusted by millions of developers around the world. Whether you’re just getting started as a developer or if you’ve been doing it for decades, Tabnine will help you code twice as fast with half the keystrokes – all in your favorite IDE. Whether you call it IntelliSense, intelliCode, autocomplete, AI-assisted code completion, AI-powered code completion, AI copilot, AI code snippets, code suggestion, code prediction, code hinting, or... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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HiFi-GAN
Generative Adversarial Networks for Efficient and High Fidelity Speech
HiFi-GAN is a GAN-based neural vocoder designed to generate high-fidelity speech waveforms from mel spectrograms with exceptional efficiency. It introduces a generator architecture tailored to model the periodic structure of speech and a set of discriminators that focus on different scales and periods of the waveform to better capture naturalness. The model targets a sweet spot between sample quality and generation speed, outperforming many previous GAN vocoders while being far faster than... -
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TFLearn
Deep learning library featuring a higher-level API for TensorFlow
TFlearn is a modular and transparent deep learning library built on top of Tensorflow. It was designed to provide a higher-level API to TensorFlow in order to facilitate and speed up experimentations while remaining fully transparent and compatible with it. Easy-to-use and understand high-level API for implementing deep neural networks, with tutorials and examples. Fast prototyping through highly modular built-in neural network layers, regularizers, optimizers, and metrics. Full transparency... -
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PyArmadillo
linear algebra library for Python
PyArmadillo - streamlined linear algebra library for Python, with emphasis on ease of use. Alternative to NumPy / SciPy. * Main page: https://pyarma.sourceforge.io * Documentation: https://pyarma.sourceforge.io/docs.html * Bug reports: https://pyarma.sourceforge.io/faq.html * Git repo: https://gitlab.com/jason-rumengan/pyarma -
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AdaNet
Fast and flexible AutoML with learning guarantees
AdaNet is a TensorFlow framework for fast and flexible AutoML with learning guarantees. AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet builds on recent AutoML efforts to be fast and flexible while providing learning guarantees. Importantly, AdaNet provides a general framework for not only learning a neural network architecture but also for learning to the ensemble to obtain even better models. At each... -
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. Rather than... -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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Delta ML
Deep learning based natural language and speech processing platform
DELTA is a deep learning-based end-to-end natural language and speech processing platform. DELTA aims to provide easy and fast experiences for using, deploying, and developing natural language processing and speech models for both academia and industry use cases. DELTA is mainly implemented using TensorFlow and Python 3. DELTA has been used for developing several state-of-the-art algorithms for publications and delivering real production to serve millions of users. It helps you to train,... -
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DETR
End-to-end object detection with transformers
PyTorch training code and pretrained models for DETR (DEtection TRansformer). We replace the full complex hand-crafted object detection pipeline with a Transformer, and match Faster R-CNN with a ResNet-50, obtaining 42 AP on COCO using half the computation power (FLOPs) and the same number of parameters. Inference in 50 lines of PyTorch. What it is. Unlike traditional computer vision techniques, DETR approaches object detection as a direct set prediction problem. It consists of a set-based... -
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Magnitude
A fast, efficient universal vector embedding utility package
A feature-packed Python package and vector storage file format for utilizing vector embeddings in machine learning models in a fast, efficient, and simple manner developed by Plasticity. It is primarily intended to be a simpler / faster alternative to Gensim but can be used as a generic key-vector store for domains outside NLP. It offers unique features like out-of-vocabulary lookups and streaming of large models over HTTP. Published in our paper at EMNLP 2018 and available on arXiv. -
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Bangla TTS
Bangla text to speech synthesis in python
Bangla text to speech Multilingual (Bangla, English) real-time ([almost] in a GPU) speech synthesis library. Installation -------------------------------------- * Install Anaconda * conda create -n new_virtual_env python==3.6.8 * conda activate new_virtual_env * pip install -r requirements.txt * While running for the first time, keep your internet connection on to download the weights of the speech synthesis models (>500 MB) * For... -
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jieba
Stuttering Chinese word segmentation
"Jaba" Chinese word segmentation, do the best Python Chinese word segmentation component. Four word segmentation modes are supported. Precise mode, which tries to cut the sentence most precisely, suitable for text analysis. Full mode, scans all the words that can be formed into words in the sentence, the speed is very fast, but the ambiguity cannot be resolved. The search engine mode, on the basis of the precise mode, divides the long words again to improve the recall rate, which is suitable... -
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Texar
Toolkit for Machine Learning, Natural Language Processing
Texar is a toolkit aiming to support a broad set of machine learning, especially natural language processing and text generation tasks. Texar provides a library of easy-to-use ML modules and functionalities for composing whatever models and algorithms. The tool is designed for both researchers and practitioners for fast prototyping and experimentation. Texar was originally developed and is actively contributed by Petuum and CMU in collaboration with other institutes. A mirror of this... -
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maskrcnn-benchmark
Fast, modular reference implementation of Instance Segmentation
Mask R-CNN Benchmark is a PyTorch-based framework that provides high-performance implementations of object detection, instance segmentation, and keypoint detection models. Originally built to benchmark Mask R-CNN and related models, it offers a clean, modular design to train and evaluate detection systems efficiently on standard datasets like COCO. The framework integrates critical components—region proposal networks (RPNs), RoIAlign layers, mask heads, and backbone architectures such as... -
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MUSE
A library for Multilingual Unsupervised or Supervised word Embeddings
MUSE is a framework for learning multilingual word embeddings that live in a shared space, enabling bilingual lexicon induction, cross-lingual retrieval, and zero-shot transfer. It supports both supervised alignment with seed dictionaries and unsupervised alignment that starts without parallel data by using adversarial initialization followed by Procrustes refinement. The code can align pre-trained monolingual embeddings (such as fastText) across dozens of languages and provides standardized... -
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automl-gs
Provide an input CSV and a target field to predict, generate a model
Give an input CSV file and a target field you want to predict to automl-gs, and get a trained high-performing machine learning or deep learning model plus native Python code pipelines allowing you to integrate that model into any prediction workflow. No black box: you can see exactly how the data is processed, and how the model is constructed, and you can make tweaks as necessary. automl-gs is an AutoML tool which, unlike Microsoft's NNI, Uber's Ludwig, and TPOT, offers a zero code/model... -
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Face Recognition
World's simplest facial recognition api for Python & the command line
Face Recognition is the world's simplest face recognition library. It allows you to recognize and manipulate faces from Python or from the command line using dlib's (a C++ toolkit containing machine learning algorithms and tools) state-of-the-art face recognition built with deep learning. Face Recognition is highly accurate and is able to do a number of things. It can find faces in pictures, manipulate facial features in pictures, identify faces in pictures, and do face recognition on a... -
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FastPhotoStyle
Style transfer, deep learning, feature transform
FastPhotoStyle is a deep learning-based image stylization framework designed to transfer the style of one photograph onto another while preserving photorealistic quality. Unlike traditional artistic style transfer methods that produce painterly outputs, this approach focuses on maintaining realistic textures, lighting, and spatial consistency. The method is based on a two-step process that includes a stylization phase followed by a smoothing operation, ensuring that the output image remains... -
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Five video classification methods
Code that accompanies my blog post outlining five video classification
Classifying video presents unique challenges for machine learning models. As I’ve covered in my previous posts, video has the added (and interesting) property of temporal features in addition to the spatial features present in 2D images. While this additional information provides us more to work with, it also requires different network architectures and, often, adds larger memory and computational demands.We won’t use any optical flow images. This reduces model complexity, training time, and... -
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Deep Learning with Keras and Tensorflow
Introduction to Deep Neural Networks with Keras and Tensorflow
Introduction to Deep Neural Networks with Keras and Tensorflow. To date tensorflow comes in two different packages, namely tensorflow and tensorflow-gpu, whether you want to install the framework with CPU-only or GPU support, respectively. NVIDIA Drivers and CuDNN must be installed and configured before hand. Please refer to the official Tensorflow documentation for further details. Since version 0.9 Theano introduced the libgpuarray in the stable release (it was previously only available in... -
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RDRPOSTagger
A Rule-based Part-of-Speech and Morphological Tagging Toolkit
RDRPOSTagger is a robust, easy-to-use and language-independent rule-based toolkit for Part-of-Speech (POS) and morphological tagging. RDRPOSTagger obtains fast performance in both learning and tagging process. RDRPOSTagger also achieves a very competitive accuracy in comparison to the state-of-the-art results. RDRPOSTagger now supports pre-trained POS and morphological tagging models for Bulgarian, Czech, Dutch, English, French, German, Hindi, Italian, Portuguese, Spanish, Swedish, Thai... -
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ProtPOS
Prediction of PROTtein Preferred Orientation on a Surface
ProtPOS is a self-contained, lightweight, and easy-to-use software package for predicting the preferred orientation of protein on a given surface upon initial adsorption. It searches quickly for the low energy protein poses in all translational and rotational degrees of freedom of the protein with respect to the surface using particle swarm optimization. Each successful run returns the lowest energy orientation of the protein on the surface in PDB format, which is readily used for MD... -
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ffnet is a fast and easy-to-use feed-forward neural network training solution for python. Many nice features are implemented: arbitrary network connectivity, automatic data normalization, very efficient training tools, network export to fortran code. Now ffnet has also a GUI called ffnetui.
