Search Results for "open-shell" - Page 5
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Showing 634 open source projects for "open-shell"
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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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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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Interpretable machine learning
Book about interpretable machine learning
This book is about interpretable machine learning. Machine learning is being built into many products and processes of our daily lives, yet decisions made by machines don't automatically come with an explanation. An explanation increases the trust in the decision and in the machine learning model. As the programmer of an algorithm you want to know whether you can trust the learned model. Did it learn generalizable features? Or are there some odd artifacts in the training data which the... -
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Lepton AI
A Pythonic framework to simplify AI service building
A Pythonic framework to simplify AI service building. Cutting-edge AI inference and training, unmatched cloud-native experience, and top-tier GPU infrastructure. Ensure 99.9% uptime with comprehensive health checks and automatic repairs. -
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sktime
A unified framework for machine learning with time series
sktime is a library for time series analysis in Python. It provides a unified interface for multiple time series learning tasks. Currently, this includes time series classification, regression, clustering, annotation, and forecasting. It comes with time series algorithms and scikit-learn compatible tools to build, tune and validate time series models. Our objective is to enhance the interoperability and usability of the time series analysis ecosystem in its entirety. sktime provides a... -
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Diffgram
Training data (data labeling, annotation, workflow) for all data types
From ingesting data to exploring it, annotating it, and managing workflows. Diffgram is a single application that will improve your data labeling and bring all aspects of training data under a single roof. Diffgram is world’s first truly open source training data platform that focuses on giving its users an unlimited experience. This is aimed to reduce your data labeling bills and increase your Training Data Quality. Training Data is the art of supervising machines through data. This includes the activities of annotation, which produces structured data; ready to be consumed by a machine learning model. ... -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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supabase-py
Python Client for Supabase. Query Postgres from Flask, Django
Python Client for Supabase. Query Postgres from Flask, Django, FastAPI. Python user authentication, security policies, edge functions, file storage, and realtime data streaming. Good first issue. -
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SimpleTuner
A general fine-tuning kit geared toward image/video/audio diffusion
...The system includes configuration-driven training processes that allow users to define datasets, model paths, and training parameters with minimal setup. SimpleTuner also emphasizes experimentation and academic collaboration, encouraging contributions and iterative improvements from the open-source community. -
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Pedalboard
A Python library for audio
pedalboard is a Python library for working with audio: reading, writing, rendering, adding effects, and more. It supports the most popular audio file formats and a number of common audio effects out of the box and also allows the use of VST3® and Audio Unit formats for loading third-party software instruments and effects. pedalboard was built by Spotify’s Audio Intelligence Lab to enable using studio-quality audio effects from within Python and TensorFlow. Internally at Spotify, pedalboard... -
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Orion
A machine learning library for detecting anomalies in signals
Orion is a machine-learning library built for unsupervised time series anomaly detection. Such signals are generated by a wide variety of systems, few examples include telemetry data generated by satellites, signals from wind turbines, and even stock market price tickers. We built this to provide one place where users can find the latest and greatest in machine learning and deep learning world including our own innovations. Abstract away from the users the nitty-gritty about preprocessing,... -
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Weights and Biases
Tool for visualizing and tracking your machine learning experiments
Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to production models. Quickly identify model regressions. Use W&B to visualize results in real time, all in a central dashboard. Focus on the interesting ML. Spend less time manually tracking results in spreadsheets and text files. Capture dataset versions with W&B Artifacts to identify how changing data affects your resulting models. Reproduce any model, with saved... -
AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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MLJAR Studio
Python package for AutoML on Tabular Data with Feature Engineering
We are working on new way for visual programming. We developed a desktop application called MLJAR Studio. It is a notebook-based development environment with interactive code recipes and a managed Python environment. All running locally on your machine. We are waiting for your feedback. The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. It is designed to save time for a data scientist. It abstracts the common way to preprocess the data,... -
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Imagen - Pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network
Implementation of Imagen, Google's Text-to-Image Neural Network that beats DALL-E2, in Pytorch. It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior... -
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ChatterBot
Machine learning, conversational dialog engine for creating chat bots
ChatterBot is a Python library that makes it easy to generate automated responses to a user’s input. ChatterBot uses a selection of machine learning algorithms to produce different types of responses. This makes it easy for developers to create chat bots and automate conversations with users. For more details about the ideas and concepts behind ChatterBot see the process flow diagram. The language independent design of ChatterBot allows it to be trained to speak any language. Additionally,... -
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Mlxtend
A library of extension and helper modules for Python's data analysis
Mlxtend (machine learning extensions) is a Python library of useful tools for day-to-day data science tasks. -
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Alibi Explain
Algorithms for explaining machine learning models
Alibi is a Python library aimed at machine learning model inspection and interpretation. The focus of the library is to provide high-quality implementations of black-box, white-box, local and global explanation methods for classification and regression models. -
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TensorFlow Datasets
TFDS is a collection of datasets ready to use with TensorFlow,
TensorFlow Datasets is a collection of datasets ready to use, with TensorFlow or other Python ML frameworks, such as Jax. All datasets are exposed as tf.data. Datasets , enabling easy-to-use and high-performance input pipelines. To get started see the guide and our list of datasets. -
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OpenVINO Training Extensions
Trainable models and NN optimization tools
OpenVINO™ Training Extensions provide a convenient environment to train Deep Learning models and convert them using the OpenVINO™ toolkit for optimized inference. When ote_cli is installed in the virtual environment, you can use the ote command line interface to perform various actions for templates related to the chosen task type, such as running, training, evaluating, exporting, etc. ote train trains a model (a particular model template) on a dataset and saves results in two files. ote... -
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tf2onnx
Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX
tf2onnx converts TensorFlow (tf-1.x or tf-2.x), keras, tensorflow.js and tflite models to ONNX via command line or python API. Note: tensorflow.js support was just added. While we tested it with many tfjs models from tfhub, it should be considered experimental. TensorFlow has many more ops than ONNX and occasionally mapping a model to ONNX creates issues. tf2onnx will use the ONNX version installed on your system and installs the latest ONNX version if none is found. We support and test ONNX... -
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High-Level Training Utilities Pytorch
High-level training, data augmentation, and utilities for Pytorch
Contains significant improvements, bug fixes, and additional support. Get it from the releases, or pull the master branch. This package provides a few things. A high-level module for Keras-like training with callbacks, constraints, and regularizers. Comprehensive data augmentation, transforms, sampling, and loading. Utility tensor and variable functions so you don't need numpy as often. Have any feature requests? Submit an issue! I'll make it happen. Specifically, any data augmentation, data... -
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Nixtla TimeGPT
TimeGPT-1: production ready pre-trained Time Series Foundation Model
TimeGPT is a production ready, generative pretrained transformer for time series. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code. Whether you're a bank forecasting market trends or a startup predicting product demand, TimeGPT democratizes access to cutting-edge predictive insights, eliminating the need for a dedicated team of machine learning engineers. A generative model for time series. TimeGPT is capable of... -
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Shapash
Explainability and Interpretability to Develop Reliable ML models
Shapash is a Python library dedicated to the interpretability of Data Science models. It provides several types of visualization that display explicit labels that everyone can understand. Data Scientists can more easily understand their models, share their results and easily document their projects in an HTML report. End users can understand the suggestion proposed by a model using a summary of the most influential criteria. -
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SKORCH
A scikit-learn compatible neural network library that wraps PyTorch
A scikit-learn compatible neural network library that wraps PyTorch. -
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supervision
We write your reusable computer vision tools
We write your reusable computer vision tools. Whether you need to load your dataset from your hard drive, draw detections on an image or video, or count how many detections are in a zone. You can count on us. -
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Materials Discovery: GNoME
AI discovers 520000 stable inorganic crystal structures for research
Materials Discovery (GNoME) is a large-scale research initiative by Google DeepMind focused on applying graph neural networks to accelerate the discovery of stable inorganic crystal materials. The project centers on Graph Networks for Materials Exploration (GNoME), a message-passing neural network architecture trained on density functional theory (DFT) data to predict material stability and energy formation. Using GNoME, DeepMind identified 381,000 new stable materials, later expanding the... -
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ktrain
ktrain is a Python library that makes deep learning AI more accessible
ktrain is a Python library that makes deep learning and AI more accessible and easier to apply. ktrain is a lightweight wrapper for the deep learning library TensorFlow Keras (and other libraries) to help build, train, and deploy neural networks and other machine learning models. Inspired by ML framework extensions like fastai and ludwig, ktrain is designed to make deep learning and AI more accessible and easier to apply for both newcomers and experienced practitioners. With only a few lines... -
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Audiomentations
A Python library for audio data augmentation
A Python library for audio data augmentation. Inspired by albumentations. Useful for deep learning. Runs on CPU. Supports mono audio and multichannel audio. Can be integrated in training pipelines in e.g. Tensorflow/Keras or Pytorch. Has helped people get world-class results in Kaggle competitions. Is used by companies making next-generation audio products. Mix in another sound, e.g. a background noise. Useful if your original sound is clean and you want to simulate an environment where...
