Search Results for "machine learning python" - Page 2
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Showing 50 open source projects for "machine learning python"
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1
Whalebrew
Homebrew, but with Docker images
...Whalebrew makes those things work with Docker, too. Whalebrew can run almost any CLI tool, but it isn't for everything (e.g. where commands must start instantly). It works particularly well for a Python app that requires C libraries, specific package versions, and other CLI tools that you don't want to clutter up your machine with. Package managers tend to be very closely tied to the system they are running on. Whalebrew packages work on any modern version of macOS, Linux, and Windows. -
2
GoNB
GoNB, a Go Notebook Kernel for Jupyter
...It already includes many goodies: cache between cell of results, contextual help and auto-complete (with gopls), compilation error context (by mousing over), bash command execution, images, html, etc. See the tutorial. It's been heavily used by the author (in developing GoMLX, a machine learning framework for Go), but should still be seen as experimental — if we hear success stories from others, we can change this. -
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Bazel Container Image Rules
Rules for building and handling Docker images with Bazel
This repository contains a set of rules for pulling down base images, augmenting them with build artifacts and assets, and publishing those images. These rules do not require / use Docker for pulling, building, or pushing images. These rules used to be docker_build, docker_push, etc. and the aliases for these (mostly) legacy names still exist largely for backwards-compatibility. We also have early-stage oci_image, oci_push, etc. aliases for folks that enjoy the consistency of a consistent... -
4
virgosun teaching support
Mentor, code c, c++, java, go, php, swift, .. DevSecOps virtual lab, .
Menor, code c, c++, java, python, go, php, swift, .., DevSecOps virtual lab, .. This software is provided as a demonstration build. Redistribution of the binary is allowed for academic evaluation only. More previously completed projects will be released incrementally as executable packages are rebuilt for public distribution. www.youtube.com/embed/fzoISpZv5d0?rel=0 -
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5
Featureform
Turn your existing data infrastructure into a feature store
Featureform allows data scientists to define, manage, and serve machine learning features across your organization. The days of untitled_128.ipynb are over. Transformations, features, and training sets can be pushed from notebooks to a centralized feature repository with metadata like name, variant, lineage, and owner. Featureform's Virtual Feature Store architecture orchestrates your data infrastructure to build and maintain your training sets and production features. ... -
6
Halfrost-Field Frostland
This is the place to blog
Halfrost-Field is a large public “knowledge and blog repository” maintained by a developer who documents a wide variety of computer-science, programming, and machine-learning content — from classic algorithms, ML fundamentals, to system design and broader engineering topics. The repository is structured like a personal technical blog/book: it contains “contents” directories with Markdown-based notes, tutorials and guides. For example, there is a full machine learning course outline (regression, neural networks, SVMs, unsupervised learning, anomaly detection, large-scale ML, even application examples like OCR), that reads like a self-study curriculum. ... -
7
Gorgonia
Gorgonia is a library that helps facilitate machine learning in Go
Write and evaluate mathematical equations involving multidimensional arrays easily. Gorgonia is a library that helps facilitate machine learning in Go. Write and evaluate mathematical equations involving multidimensional arrays easily. If this sounds like Theano or TensorFlow, it's because the idea is quite similar. Specifically, the library is pretty low-level, like Theano, but has higher goals like Tensorflow. The primary goal for Gorgonia is to be a highly performant machine learning/graph computation-based library that can scale across multiple machines. ... -
8
spaGO
Self-contained Machine Learning and Natural Language Processing lib
A Machine Learning library written in pure Go designed to support relevant neural architectures in Natural Language Processing. Spago is self-contained, in that it uses its own lightweight computational graph both for training and inference, easy to understand from start to finish. The core module of Spago relies only on testify for unit testing. -
9
Lingua-Go
The most accurate natural language detection library for Go
...Other use cases, for instance, might include routing e-mails to the right geographically located customer service department, based on the e-mails' languages. Language detection is often done as part of large machine-learning frameworks or natural language processing applications. In cases where you don't need the full-fledged functionality of those systems or don't want to learn the ropes of those, a small flexible library comes in handy. -
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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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aqueduct LLM
Aqueduct allows you to run LLM and ML workloads on any infrastructure
Aqueduct is an MLOps framework that allows you to define and deploy machine learning and LLM workloads on any cloud infrastructure. Aqueduct is an open-source MLOps framework that allows you to write code in vanilla Python, run that code on any cloud infrastructure you'd like to use, and gain visibility into the execution and performance of your models and predictions. Aqueduct's Python native API allows you to define ML tasks in regular Python code. ... -
12
KubeOperator
An open source, lightweight Kubernetes distribution
...Support online environment and offline environment deployment. Provides a visual web UI. Supports cluster planning, deployment and operations. Easily run workloads like machine learning, high-performance computing, and more. Quickly deploy and manage applications in K8S. Only two steps to complete the KubeOperator installation and deployment. -
13
cortex
Production infrastructure for machine learning at scale
Cortex is an open-source platform designed for building, deploying, and managing machine learning applications in production environments. The framework provides infrastructure tools that allow developers to transform trained machine learning models into scalable web services. Cortex handles many operational challenges associated with deploying AI systems, such as managing dependencies, orchestrating data pipelines, and scaling services under load. -
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Amazon SageMaker Operators Kubernetes
Amazon SageMaker operator for Kubernetes
Amazon SageMaker is a fully managed machine learning service. With SageMaker, data scientists and developers can quickly and easily build and train machine learning models, and then directly deploy them into a production-ready hosted environment. It provides an integrated Jupyter authoring notebook instance for easy access to your data sources for exploration and analysis, so you don't have to manage servers. -
15
Pigo
Fast face detection, pupil/eyes localization
Fast face detection, pupil/eyes localization and facial landmark points detection library in pure Go. Pigo is a pure Go face detection, pupil/eyes localization and facial landmark points detection library based on the Pixel Intensity Comparison-based Object detection paper. The reason why Pigo has been developed is because almost all of the currently existing solutions for face detection in the Go ecosystem are purely bindings to some C/C++ libraries like OpenCV or dlib, but calling a C... -
16
Horusec
Open source tool that improves identification of vulnerabilities
Horusec is an open source tool that performs a static code analysis to identify security flaws during the development process. Currently, the languages for analysis are C#, Java, Kotlin, Python, Ruby, Golang, Terraform, Javascript, Typescript, Kubernetes, PHP, C, HTML, JSON, Dart, Elixir, Shell, Nginx. The tool has options to search for key leaks and security flaws in all your project's files, as well as in Git history. Horusec can be used by the developer through the CLI and by the... -
17
Kite
Primary Kite repo, private bits replaced with XXXXXXX
...We used a variety of infrastructure, on a mix of cloud platforms, depending on what was most economical, though it was mostly on AWS. You should be able to develop, build, and test Kite entirely on your local machine. However, we do have cloud instances & VMs available for running larger jobs and for testing our cloud services. We bundle a lot of pre-computed datasets & machine learning models into the Kite app through the use of a custom filemap & encoding on top of go-bindata. The data, located in kite-go/client/datadeps, is kept in Git-LFS. -
18
elastic-jupyter-operator
Cloud-native way to provide elastic Jupyter Notebooks on Kubernetes
Jupyter is a free, open-source, interactive web tool known as a computational notebook, which researchers can use to combine software code, computational output, explanatory text, and multimedia resources in a single document. For data scientists and machine learning engineers, Jupyter has emerged as a de facto standard. At the same time, there has been growing criticism that the way notebooks are being used leads to low resource utilization. GPU and other hardware resources will be bound to the specified notebooks even if the data scientists do not need them currently. This project proposes some Kubernetes CRDs to solve these problems. -
19
GoWebSocket
golang supports million-connection distributed chat (IM) system
...The project uses gRPC for communication between program components and is structured to support distributed real-time messaging rather than a single-process chat demo. Its documentation highlights single-machine million-connection goals, making performance and concurrency central to the design. gowebsocket is useful for developers studying large-scale WebSocket systems, chat backends, connection management, and Go network programming. It is best treated as a technical reference and learning project for distributed real-time architecture. -
20
SQLFlow
SQL compiler bridging databases and machine learning workflows
...By embedding machine learning operations into SQL, it removes the need for users to switch between programming languages such as Python or R, simplifying the overall workflow. SQLFlow also supports model training, prediction, and explanation tasks, allowing data practitioners to work entirely within a familiar query interface. -
21
Olivia
Your new best friend powered by an artificial neural network
Olivia is an open-source chatbot built in Golang using Machine Learning technologies. Its goal is to provide a free and open-source alternative to big services like DialogFlow. You can chat with her by speaking (STT) or writing, she replies with a text message but you can enable her voice (TTS). Olivia can listen to you by saying “Hey Olivia” or clicking on the central button. She speaks to reply to you unless you've disabled her voice. -
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Docker Machine
Machine management for a container-centric world
Docker Machine is a tool that lets you install Docker Engine on virtual hosts, and manage the hosts with docker-machine commands. You can use Machine to create Docker hosts on your local Mac or Windows box, on your company network, in your data center, or on cloud providers like Azure, AWS, or DigitalOcean. Using docker-machine commands, you can start, inspect, stop, and restart a managed host, upgrade the Docker client and daemon, and configure a Docker client to talk to your host. Point... -
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lgo
Interactive Go programming with Jupyter
lgo is an open-source programming environment that enables interactive Go programming within Jupyter Notebook environments. The project provides a Jupyter kernel for the Go programming language, allowing developers to write and execute Go code interactively in notebook cells similar to how Python is used in data science workflows. This environment combines the strong performance and concurrency features of the Go language with the exploratory and iterative style of notebook-based... -
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The Google Cloud Developer's Cheat Sheet
Cheat sheet for Google Cloud developers
Every product in the Google Cloud family described in <=4 words (with liberal use of hyphens and slashes) by the Google Developer Relations Team. This list only includes products that are publicly available. There are several products in pre-release/private-alpha that will not be included until they go public beta or GA. Many of these products have a free tier. There is also a free trial that will enable you try almost everything. API platforms and ecosystems, developer and management tools,... -
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FIND3
High-precision indoor positioning framework, version 3
...(previously just WiFi). Passive scanning built-in (previously required a separate server). Support for Bluetooth scanning in scanning utility (previously just WiFi). Meta-learning with 10 different machine learning classifiers (previously just three). Client uses Websockets+React which reduces bandwidth (and coding complexity). Rolling compression of MAC addresses for much smaller on-disk databases. Data storage in SQLite-database (previously it was BoltDB). Released under MIT license (more commercially compatible than AGPL). ...
