Search Results for "neural python" - Page 5
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Showing 225 open source projects for "neural python"
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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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Alpa
Training and serving large-scale neural networks
Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code. -
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Sockeye
Sequence-to-sequence framework, focused on Neural Machine Translation
Sockeye is an open-source sequence-to-sequence framework for Neural Machine Translation built on PyTorch. It implements distributed training and optimized inference for state-of-the-art models, powering Amazon Translate and other MT applications. For a quickstart guide to training a standard NMT model on any size of data, see the WMT 2014 English-German tutorial. If you are interested in collaborating or have any questions, please submit a pull request or issue. You can also send questions... -
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NeuronetExperimenter
NeuronetExperimenter simulates the activity of biological neurons
The NeuronetExperimenter software can be used to quickly simulate large sets of biological neurons arranged with arbitrary network connectivity. The software makes it easy to investigate the behaviors of large, complex, neural networks, especially when starting from XPPAUT models (http://www.math.pitt.edu/~bard/xpp/xpp.html). The software is very flexible and allows users to develop multiple neuron types with different constituent differential equations describing their behavior. Any... -
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Conscious Artificial Intelligence
It's possible for machines to become self-aware.
This project is a quest for conscious artificial intelligence. A number of prototypes will be developed as the project progresses. This project has 2 subprojects: Object Pascal based CAI NEURAL API - https://github.com/joaopauloschuler/neural-api Python based K-CAI NEURAL API - https://github.com/joaopauloschuler/k-neural-api A video from the first prototype has been made: http://www.youtube.com/watch?v=qH-IQgYy9zg Above video shows a popperian agent collecting mining ore from 3... -
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ManimML
ManimML is a project focused on providing animations
ManimML is a project focused on providing animations and visualizations of common machine-learning concepts with the Manim Community Library. Please check out our paper. We want this project to be a compilation of primitive visualizations that can be easily combined to create videos about complex machine-learning concepts. Additionally, we want to provide a set of abstractions that allow users to focus on explanations instead of software engineering. -
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GNNePCSAFT
Smart Thermodynamic Modeling with Graph Neural Networks
Our project harnesses the power of Graph Neural Network (GNN) to estimate pure-component parameters of the state-of-the-art Equation of State, PC-SAFT. We aim to empower users to leverage this robust equation without the need for prior experimental data, revolutionizing the calculation of thermodynamic properties and enhancing process simulations. FeOS is used for the PC-SAFT calculations. The estimated parameters can be used in DWSIM and Aspen HYSYS process simulators. -
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Eugraphios
Free, portable desktop Computer-Assisted Translation (CAT) tool.
Eugraphios is a free, portable desktop Computer-Assisted Translation (CAT) tool designed for freelancers. Whether you're translating documents, websites, or software, Eugraphios is designed to meet your needs and exceed your expectations. With a focus on intuitive design and user-friendly interfaces, Eugraphios aims to eliminate the complexity that often hinders professionals and beginners in the translation field. By providing a seamless and enjoyable experience, this tool empowers users... -
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DeepCTR
Package of deep-learning based CTR models
DeepCTR is a Easy-to-use,Modular and Extendible package of deep-learning based CTR models along with lots of core components layers which can be used to easily build custom models. You can use any complex model with model.fit(), and model.predict(). Provide tf.keras.Model like interface for quick experiment. Provide tensorflow estimator interface for large scale data and distributed training. It is compatible with both tf 1.x and tf 2.x. With the great success of deep learning,DNN-based... -
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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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DeepCTR-Torch
Easy-to-use,Modular and Extendible package of deep-learning models
... features and some dense numerical features. Low-order Extractor learns feature interaction through product between vectors. Factorization-Machine and it’s variants are widely used to learn the low-order feature interaction. High-order Extractor learns feature combination through complex neural network functions like MLP, Cross Net, etc. -
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Emb-GAM
An interpretable and efficient predictor using pre-trained models
Deep learning models have achieved impressive prediction performance but often sacrifice interpretability, a critical consideration in high-stakes domains such as healthcare or policymaking. In contrast, generalized additive models (GAMs) can maintain interpretability but often suffer from poor prediction performance due to their inability to effectively capture feature interactions. In this work, we aim to bridge this gap by using pre-trained neural language models to extract embeddings... -
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Auto-PyTorch
Automatic architecture search and hyperparameter optimization
While early AutoML frameworks focused on optimizing traditional ML pipelines and their hyperparameters, another trend in AutoML is to focus on neural architecture search. To bring the best of these two worlds together, we developed Auto-PyTorch, which jointly and robustly optimizes the network architecture and the training hyperparameters to enable fully automated deep learning (AutoDL). Auto-PyTorch is mainly developed to support tabular data (classification, regression) and time series data... -
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HealthFusion
AI Disease Detections System
... diseases using the power of AI. HealthFusion is a user-friendly app that can be accessed from the comfort of homes, making it accessible to everyone. The use of advanced technologies such as Convolutional Neural Networks, Random Forest, and XGBoost allows for accurate and timely detection of diseases, leading to better patient outcomes. -
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nlpaug
Data augmentation for NLP
This Python library helps you with augmenting nlp for your machine learning projects. Visit this introduction to understand Data Augmentation in NLP. Augmenter is the basic element of augmentation while Flow is a pipeline to orchestra multi augmenters together. -
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Fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python
... in the new FullyShardedDataParallel (FSDP) wrapper provided by fairscale. Fairseq can be extended through user-supplied plug-ins. Models define the neural network architecture and encapsulate all of the learnable parameters. Criterions compute the loss function given the model outputs and targets. Tasks store dictionaries and provide helpers for loading/iterating over Datasets, initializing the Model/Criterion and calculating the loss. -
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Chainer
A flexible deep learning framework
Chainer is a Python-based deep learning framework. It provides automatic differentiation APIs based on dynamic computational graphs as well as high-level APIs for neural networks. -
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G2SConverter
Convert models from GoldSource engine to Source engine with AI
Convert models from GoldSource engine to the Source engine with AI. This utility converts GoldSource engine models to Source engine models. A feature of this utility is the ability to improve the quality of textures of models using Upscaling, deblurring, and normal map generating. All operations to improve the quality of textures are performed by neural networks. To improve the quality of the texture, it is first Upscaled using RealESRGAN. The user can select scaling factor: x2, x4 or x8... -
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ruDALL-E
Generate images from texts. In Russian
... in Russian and other languages. You can even combine different languages within a single query. This neural network has been developed and trained by Sber AI researchers in close collaboration with scientists from Artificial Intelligence Research Institute using joined datasets by Sber AI and SberDevices. Russian text-to-image model that generates images from text. The architecture is the same as ruDALL-E XL. Even more parameters in the new version. -
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Deep Daze
Simple command line tool for text to image generation
Simple command-line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network). In true deep learning fashion, more layers will yield better results. Default is at 16, but can be increased to 32 depending on your resources. Technique first devised and shared by Mario Klingemann, it allows you to prime the generator network with a starting image, before being steered towards the text. Simply specify the path to the image you wish to use... -
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TensorFlow Backend for ONNX
Tensorflow Backend for ONNX
Open Neural Network Exchange (ONNX) is an open standard format for representing machine learning models. ONNX is supported by a community of partners who have implemented it in many frameworks and tools. TensorFlow Backend for ONNX makes it possible to use ONNX models as input for TensorFlow. The ONNX model is first converted to a TensorFlow model and then delegated for execution on TensorFlow to produce the output. This is one of the two TensorFlow converter projects which serve different... -
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Machine Learning PyTorch Scikit-Learn
Code Repository for Machine Learning with PyTorch and Scikit-Learn
Initially, this project started as the 4th edition of Python Machine Learning. However, after putting so much passion and hard work into the changes and new topics, we thought it deserved a new title. So, what’s new? There are many contents and additions, including the switch from TensorFlow to PyTorch, new chapters on graph neural networks and transformers, a new section on gradient boosting, and many more that I will detail in a separate blog post. For those who are interested in knowing what... -
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Argos Translate
Open-source offline translation library written in Python
Argos Translate uses OpenNMT for translations and can be used as either a Python library, command-line, or GUI application. Argos Translate supports installing language model packages which are zip archives with a ".argosmodel" extension containing the data needed for translation. LibreTranslate is an API and web-app built on top of Argos Translate. Argos Translate also manages automatically pivoting through intermediate languages to translate between languages that don't have a direct... -
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Aquila DB
An easy to use Neural Search Engine
Aquila DB is a Neural search engine. In other words, it is a database to index Latent Vectors generated by ML models along with JSON Metadata to perform k-NN retrieval. It is dead simple to set up, language-agnostic, and drop in addition to your Machine Learning Applications. Aquila DB, as of current features is a ready solution for Machine Learning engineers and Data scientists to build Neural Information Retrieval applications out of the box with minimal dependencies. -
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Robust Video Matting (RVM)
Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX
We introduce a robust, real-time, high-resolution human video matting method that achieves new state-of-the-art performance. Our method is much lighter than previous approaches and can process 4K at 76 FPS and HD at 104 FPS on an Nvidia GTX 1080Ti GPU. Unlike most existing methods that perform video matting frame-by-frame as independent images, our method uses a recurrent architecture to exploit temporal information in videos and achieves significant improvements in temporal coherence and... -
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Parakeet
PAddle PARAllel text-to-speech toolKIT
PAddle PARAllel text-to-speech toolKIT (supporting Tacotron2, Transformer TTS, FastSpeech2/FastPitch, SpeedySpeech, WaveFlow and Parallel WaveGAN) Parakeet aims to provide a flexible, efficient and state-of-the-art text-to-speech toolkit for the open-source community. It is built on PaddlePaddle dynamic graph and includes many influential TTS models. In order to facilitate exploiting the existing TTS models directly and developing the new ones, Parakeet selects typical models and provides...
