Search Results for "big data"
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12 projects for "big data" with 2 filters applied:
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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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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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Big-AGI
AI suite powered by state-of-the-art models and providing advanced AI
...The workspace includes advanced features like Beam, which enables multi-model consensus and comparative responses to improve reliability and reduce hallucination, and robust persona management to tailor responses to specific roles or workflows. Big-AGI can be self-hosted or deployed in cloud environments, giving users full control over data and model access limits and avoiding vendor lock-in. -
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DATA SCIENCE ROADMAP
Data Science Roadmap from A to Z
DATA SCIENCE ROADMAP is an educational repository designed to guide learners through the process of becoming proficient in data science and machine learning. The project presents a structured roadmap that outlines the knowledge and skills required for different stages of a data science career. Topics typically include programming with Python, statistics, mathematics, machine learning algorithms, data visualization, and big data technologies. ... -
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LlamaIndex
Central interface to connect your LLM's with external data
LlamaIndex (GPT Index) is a project that provides a central interface to connect your LLM's with external data. LlamaIndex is a simple, flexible interface between your external data and LLMs. It provides the following tools in an easy-to-use fashion. Provides indices over your unstructured and structured data for use with LLM's. These indices help to abstract away common boilerplate and pain points for in-context learning. Dealing with prompt limitations (e.g. 4096 tokens for Davinci) when the context is too big. ... -
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Sail
A drop-in Apache Spark replacement written in Rust
Sail is an open-source distributed computation framework designed to unify batch processing, stream processing, and AI workloads into a single, high-performance engine. It is built entirely in Rust, eliminating JVM overhead and enabling predictable performance, fast startup times, and improved memory safety compared to traditional big data frameworks. Sail is compatible with the Spark Connect protocol, which means existing Spark SQL and DataFrame workloads can run without code changes, making adoption seamless for teams already using Spark-based pipelines. The framework is designed to operate across a variety of environments, including local machines, Kubernetes clusters, and cloud deployments, allowing flexible scaling based on workload requirements. ... -
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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AlphaTree
DNN && GAN && NLP && BIG DATA
AlphaTree is an educational repository that provides a visual roadmap of deep learning models and related artificial intelligence technologies. The project focuses on explaining the historical development and relationships between major neural network architectures used in modern machine learning. It presents diagrams and documentation describing the evolution of models such as LeNet, AlexNet, VGG, ResNet, DenseNet, and Inception networks. The repository organizes these architectures into a... -
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MOA - Massive Online Analysis
Big Data Stream Analytics Framework.
A framework for learning from a continuous supply of examples, a data stream. Includes classification, regression, clustering, outlier detection and recommender systems. Related to the WEKA project, also written in Java, while scaling to adaptive large scale machine learning. -
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SparrowRecSys
A Deep Learning Recommender System
SparrowRecSys is an open-source deep learning recommendation system framework designed to demonstrate the architecture and implementation of modern industrial-scale recommender systems. The project integrates multiple machine learning models and data processing pipelines to simulate how real-world recommendation platforms operate. It includes components for offline data processing, feature engineering, model training, real-time data updates, and online recommendation services. SparrowRecSys... -
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surpriver
Find big moving stocks before they move using machine learning
surpriver is a machine learning project designed to identify unusual stock market activity that may precede large price movements. The system analyzes historical stock price and volume data to detect anomalies that could indicate potential trading opportunities. By applying machine learning techniques to market indicators, the tool attempts to identify patterns in trading behavior that deviate significantly from normal market activity. These anomalies are interpreted as signals that a stock... -
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H2O-3
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning
...H2O-3 integrates with big data technologies such as Hadoop and Apache Spark, enabling organizations to run machine learning workflows on large-scale data infrastructure. The platform also includes a web-based interface called Flow that allows users to build models interactively through notebooks and visual tools. -
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Spark Python Notebooks
Apache Spark & Python (pySpark) tutorials for Big Data Analysis
Spark Python Notebooks is a curated collection of example Jupyter notebooks designed to help developers and data engineers learn Apache Spark using Python in an interactive environment. Rather than only providing static code files, this project uses notebooks to teach practical data processing workflows, exposing users to real Spark programming patterns like working with RDDs, DataFrames, and distributed computations. These notebooks often demonstrate how to transform, analyze, and visualize large datasets using PySpark APIs, which mirrors many real-world big data use cases. ... -
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pyIRDG
IMDb Relational Dataset Generator
pyIRDG is a program written in Python to generate relational datasets in Prolog format. It uses data from the Internet Movie Database in combination with IMDbPY as backend. A graphical user interface written in pyQt allows the user to link multiple entities together as model for the generation process. The big four entities are Title, Person, Company and Character. Many attributes can be chosen for adding to the output .pl file. -
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SURF-nanodots
Very basic computer vision program
This was my first big programming project. I'd like to clean it up and improve the back end design when time permits. See the wiki for known issues and more information. A computer vision program for analysis of magnetic data collected by a scanning probe microscope. Originated in summer 2007 as a collection of C compiled for Matlab (MEX) files and was eventually ported to a standalone C++ application with a GUI created in Qt.
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