Search Results for "ekho-data" - Page 10
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Showing 3592 open source projects for "ekho-data"
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FinRobot
An Open-Source AI Agent Platform for Financial Analysis using LLMs
FinRobot is an open-source AI framework focused on automating financial data workflows by combining data ingestion, feature engineering, model training, and automated decision-making pipelines tailored for quantitative finance applications. It provides developers and quants with structured modules to fetch market data, process time series, generate technical indicators, and construct features appropriate for machine learning models, while also supporting backtesting and evaluation metrics to measure strategy performance. ... -
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WriteTeX
An Inkscape extension: Latex/Tex editor for Inkscape
Due to an incompatible change of the Inkscape extension API, this extension has to split into two versions. For Inkscape versions lower than 1.0, users should use the files in the 0.9.x folder, the other users should use files in the 1.0.x folder. -
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DVC
Data Version Control | Git for Data & Models
DVC is built to make ML models shareable and reproducible. It is designed to handle large files, data sets, machine learning models, and metrics as well as code. Version control machine learning models, data sets and intermediate files. DVC connects them with code and uses Amazon S3, Microsoft Azure Blob Storage, Google Drive, Google Cloud Storage, Aliyun OSS, SSH/SFTP, HDFS, HTTP, network-attached storage, or disc to store file contents. -
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Freqtrade
Free, open source crypto trading bot
...Do not hesitate to read the source code and understand the mechanisms of this bot, algorithms, and techniques implemented in it. Write your strategy in python, using pandas. Example strategies to inspire you are available in the strategy repository. Download historical data of the exchange and the markets you may want to trade with. Find the best parameters for your strategy using hyper optimization which employs machining learning methods. -
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Astropy
Repository for the Astropy core package
...It is at the core of the Astropy Project, which aims to enable the community to develop a robust ecosystem of affiliated packages covering a broad range of needs for astronomical research, data processing, and data analysis. -
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Blackbird
OSINT tool for finding accounts across 600+ sites by username or email
...The project focuses on helping investigators, researchers, and security professionals quickly discover where a specific identity appears on the internet. It performs reverse searches across more than 600 websites by leveraging data from the community-driven WhatsMyName project, which improves detection accuracy and reduces false positives. The tool operates primarily through a command line interface, allowing users to run automated searches and gather results from many platforms in a single process. Blackbird also includes an optional AI-powered profiling feature that analyzes discovered sites to generate behavioral and technical insights about a user’s online presence. ... -
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SurfSense
Connect any LLM to your internal knowledge sources
...The platform also supports advanced retrieval augmented generation (RAG) capabilities, enabling powerful search and citation features that help answer questions with contextually relevant data. -
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harmonypy
Integrate multiple high-dimensional datasets with fuzzy k-means
Harmony is an algorithm for integrating multiple high-dimensional datasets. harmonypy is a port of the harmony R package by Ilya Korsunsky. Harmony is a general-purpose R package with an efficient algorithm for integrating multiple data sets. It is especially useful for large single-cell datasets such as single-cell RNA-seq. -
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MindsDB
Making Enterprise Data Intelligent and Responsive for AI
MindsDB is an AI data solution that enables humans, AI, agents, and applications to query data in natural language and SQL, and get highly accurate answers across disparate data sources and types. MindsDB connects to diverse data sources and applications, and unifies petabyte-scale structured and unstructured data. Powered by an industry-first cognitive engine that can operate anywhere (on-prem, VPC, serverless), it empowers both humans and AI with highly informed decision-making capabilities. ... -
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OpenDataMCP
Connect any Open Data to any LLM with Model Context Protocol
An initiative aimed at connecting open datasets to Large Language Models (LLMs) using the Model Context Protocol, facilitating seamless access and integration of public data into AI applications. -
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BambooAI
A Python library powered by Language Models (LLMs)
BambooAI is a Python library powered by large language models (LLMs) for conversational data discovery and analysis, allowing users to interact with data through natural language. -
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The FreeMoCap Project
Free Motion Capture for Everyone
...FreeMoCap includes tools for calibration, recording, processing, and visualization, allowing users to move from raw footage to structured motion data within a single ecosystem. Because it is open and extensible, researchers and developers can adapt the pipeline for specialized motion analysis or integrate it into animation workflows. -
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python-benedict
dict subclass with keylist/keypath support
python-benedict is a dict subclass with keylist/keypath/keyattr support, I/O shortcuts (base64, cli, csv, ini, json, pickle, plist, query-string, toml, xls, xml, yaml) and many utilities... for humans, obviously. -
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AutoKeras
AutoML library for deep learning
AutoKeras: An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras is to make machine learning accessible to everyone. AutoKeras only support Python 3. If you followed previous steps to use virtualenv to install tensorflow, you can just activate the virtualenv. Currently, AutoKeras is only compatible with Python >= 3.7 and TensorFlow >= 2.8.0. AutoKeras supports several tasks with extremely simple interface. -
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AstronRPA
Agent-ready RPA suite with visual workflow automation tools engine
...It enables automation of common desktop software and browser-based tasks, making it suitable for repetitive business operations and system integrations. Astron RPA includes a large library of reusable components that handle tasks such as user interface operations, data processing, and system interactions, allowing workflows to be assembled from modular building blocks. Astron RPA also integrates with intelligent agent systems so that automated processes and AI-driven workflows can work together in broader automation scenarios. -
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DocsGPT
Private AI platform for agents, enterprise search and RAG pipelines
DocsGPT is an open-source AI platform for deploying private RAG pipelines, AI agents, and enterprise search on your own infrastructure. Connect any data source (PDFs, DOCX, CSV, Excel, HTML, audio, GitHub, databases, URLs) and get accurate, hallucination-free answers with source citations. Choose your LLM: OpenAI, Anthropic, Google Gemini, or local models. Works with Qdrant, MongoDB, and Elasticsearch and more. Deploy via Docker or Kubernetes with full data sovereignty. Build embeddable chat and search widgets, automate multi-step workflows with AI agents, and integrate via Slack, Telegram, Discord, or REST API. ... -
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Cython
The most widely used Python to C compiler
...Easily tune readable Python code into plain C performance by adding static type declarations, also in Python syntax. Use combined source code level debugging to find bugs in your Python, Cython, and C code. Interact efficiently with large data sets, e.g. using multi-dimensional NumPy arrays. Quickly build your applications within the large, mature, and widely used CPython ecosystem. Integrate natively with existing code and data from legacy, low-level or high-performance libraries and applications. The Cython language is a superset of the Python language that additionally supports calling C functions and declaring C types on variables and class attributes. -
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Matrix
Multi-Agent daTa geneRation Infra and eXperimentation framework
Matrix is a distributed, large-scale engine for multi-agent synthetic data generation and experiments: it provides the infrastructure to run thousands of “agentic” workflows concurrently (e.g. multiple LLMs interacting, reasoning, generating content, data-processing pipelines) by leveraging distributed computing (like Ray + cluster management). The idea is to treat data generation as a “data-to-data” transformation: each input item defines a task, and the runtime orchestrates asynchronous, peer-to-peer agent workflows, avoiding global synchronization bottlenecks. ... -
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OpenBB Terminal
Investment research for everyone, anywhere
...The MIT Open Source license allows any user to fork the project to either add features to the broader community or create their own customized terminal version. The terminal allows for users to import their own proprietary datasets to use on our econometric menu. In addition, users are allowed to export any type of data to any type of format whether that is raw data in Excel or an image in PNG. This is ideal for finance content creation. Create notebook templates (through papermill) which can be run on different tickers. This level of automation allows to speed up the development of your investment thesis and reduce human error. -
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JSON_REPAIR
A python module to repair invalid JSON from LLMs
...The repair process can also be combined with optional JSON Schema validation to enforce structural constraints and ensure the output conforms to expected data types and formats. Developers can integrate the library into applications as a drop-in replacement for standard JSON parsing functions, allowing systems to tolerate imperfect structured data without crashing. -
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NeMo Curator
Scalable data pre processing and curation toolkit for LLMs
NeMo Curator is a Python library specifically designed for fast and scalable dataset preparation and curation for large language model (LLM) use-cases such as foundation model pretraining, domain-adaptive pretraining (DAPT), supervised fine-tuning (SFT) and paramter-efficient fine-tuning (PEFT). It greatly accelerates data curation by leveraging GPUs with Dask and RAPIDS, resulting in significant time savings. The library provides a customizable and modular interface, simplifying pipeline expansion and accelerating model convergence through the preparation of high-quality tokens. At the core of the NeMo Curator is the DocumentDataset which serves as the the main dataset class. ... -
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PaddleX
PaddlePaddle End-to-End Development Toolkit
...Users only need to put pictures belonging to the same category in the same folder. When the model is trained, we need to divide the training set, the validation set and the test set. Therefore, we need to divide the above data. Using the paddlex command, the data set can be randomly divided into 70% training set, 20% validation set and 10% test set. If you use the PaddleX visualization client for model training, the data set division function is integrated in the client, and you do not need to use command division by yourself. -
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leafmap
A Python package for interactive mapping and geospatial analysis
...However, not everyone in the geospatial community has access to the GEE cloud computing platform. Leafmap is designed to fill this gap for non-GEE users. It is a free and open-source Python package that enables users to analyze and visualize geospatial data with minimal coding in a Jupyter environment, such as Google Colab, Jupyter Notebook, and JupyterLab. Leafmap is built upon several open-source packages, such as folium and ipyleaflet (for creating interactive maps), WhiteboxTools and whiteboxgui (for analyzing geospatial data), and ipywidgets (for designing interactive graphical user interface [GUI]). -
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SageMaker Spark Container
Docker image used to run data processing workloads
Apache Spark™ is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing. -
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Instill Core
Instill Core is a full-stack AI infrastructure tool for data
Instill Core is an open-source, full-stack AI infrastructure platform designed to orchestrate data pipelines, machine learning models, and unstructured data processing into a unified, production-ready system. It provides an end-to-end solution that enables developers to build, deploy, and manage AI-powered applications without needing to manually stitch together multiple tools across the data and model lifecycle. The platform focuses heavily on handling unstructured data such as documents, images, audio, and video, transforming them into AI-ready formats through integrated ETL pipelines and processing workflows. ...