Программное обеспечение для машинного обучения
5 Отзывов
Reproducible Experiment Platform (REP) is a software infrastructure to support collaborative ecosystem for computational science it is a Python based solution for research teams that allows running computational experiments on shared datasets, obtaining repeatable results, and consistent comparisons of the obtained results.
5 Отзывов
Pattern Recognition and Machine Learning is a Matlab implementation of the algorithms.
5 Отзывов
Entity resolution is essential for higher quality analytics, reporting and compliance. We create the most complete and accurate views of people, organizations and relationships from all of your data. Our entity resolution software is the most advanced, affordable and easy to use solution.
5 Отзывов
MLDB is an open-source database designed for machine learning that can be install in any device and send commands over a RESTful API to store data, explore it using SQL, then train machine learning models and expose them as APIs.
3 Отзыва
Crab as known as scikits.recommender is a Python framework for building recommender engines that integrate with the world of scientific Python packages (numpy, scipy, matplotlib), provide a rich set of components from which user can construct a customized recommender system from a set of algorithms and be usable in various contexts: ** science and…
Узнайте больше об этой компании
3 Отзыва
From trained ML models to production-grade prediction services with just a few lines of code
3 Отзыва
MorphL is an AI platform that helps e-commerce companies make intelligent decisions, accelerate growth, and personalize experiences. MorphL consists of a suite of 10 machine learning models that are fully automated, that can be used across the enterprise, across the full customer journey, and are platform agnostic. MorphL is funded via Techstars…
Узнайте больше об этой компании
3 Отзыва
Numenta is a machine intelligence solution that delivers capabilities and demonstrates a computing approach based on biological learning principles to help you manage your business.
3 Отзыва
3 Отзыва
OpenBlender’s proprietary technology is the only one to enable data scientists to efficiently enrich their machine learning models with meaningful external data from any source (variables from news, social media, financial markets, weather, demographics, etc.) to greatly improve performance. OpenBlender automatically profiles, cleans and transforms…
Узнайте больше об этой компании
3 Отзыва
OpenAI Gym is a toolkit for developing and comparing reinforcement learning algorithms that supports teaching agents everything from walking to playing games like Pong or Go.
2 Отзыва
Disco is a lightweight, open-source framework for distributed computing based on the MapReduce paradigm it distributes and replicates data, and schedules jobs efficiently it includes the tools need to index billions of data points and query them in real-time.
2 Отзыва
Alie is Muvi’s AI-powered Recommendation Engine useful for website & mobile applications. Alie captures and analyzes user data to make accurate product/content recommendations in real-time as per individual user’s tastes and preferences. Best suited for streaming services, e-commerce sites, and EdTech portals, Alie is known for hassle-free integration…
Узнайте больше об этой компании
2 Отзыва
Vision Cloud is a native media recognition AI platform that builds Machine Wisdom from intelligence to transform business operations.
2 Отзыва
Learn, test and prototype AI inference workloads using Intel® DevCloud for the Edge, which includes a preinstalled and preconfigured version of the Intel® Distribution of OpenVINOTM toolkit and AI pipeline software. Access tutorials, sample applications and pretrained models via a Jupyter Notebook environment and execute workloads on a wide range of…
Узнайте больше об этой компании
2 Отзыва
Verfacto is a machine-learning tool that unifies customer data from scattered sources, blends it with behavioural data, and turns into insights that help e-commerce businesses to approach the right audience with the right message, adjust acquisition channels according to customers lifetime value, upsell and cross-sell effectively, make discounts only if…
Узнайте больше об этой компании
2 Отзыва
Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks.
2 Отзыва
Paradise provides multi-attribute analysis for seismic interpretation using neural networks/machine learning.
2 Отзыва
Recommendation360TM Retail is a recommendation engine that enables e-commerce retailers to generate hyper-personalized product recommendations to their customers.
2 Отзыва
At present, there is a growing need for AI that can be used by incorporating it into the edge device side, instead of the conventional AI that is processed on the cloud side, such as deep learning. This is called "edge AI". As a specific technical difference, when the conventional AI learns on the cloud server side and communicates with the edge side…
Узнайте больше об этой компании- Программное обеспечение для машинного обучения — это набор инструментов, сред и алгоритмов, предназначенных для облегчения разработки и развертывания моделей машинного обучения. Он предоставляет необходимую инфраструктуру и ресурсы для обучения, проверки и применения методов машинного обучения к различным наборам данных.
- Программное обеспечение для машинного обучения обычно предлагает такие функции, как предварительная обработка данных, выбор и оценка модели, реализация алгоритма и возможности развертывания модели. Это позволяет пользователям обрабатывать и анализировать данные, обучать модели и делать прогнозы или классификации на основе входных данных.
- Доступно несколько популярных программных сред машинного обучения, включая TensorFlow, PyTorch, scikit-learn, Keras и Caffe. Эти платформы предоставляют широкий спектр инструментов и библиотек для упрощения разработки и внедрения моделей машинного обучения.
- В то время как программное обеспечение для машинного обучения традиционно требует определенного уровня технических знаний и навыков программирования, в настоящее время существуют удобные платформы и инструменты, которые позволяют пользователям, не являющимся техническими специалистами, использовать возможности машинного обучения. Эти платформы часто предоставляют графический интерфейс и готовые модели, которые можно настраивать без сложного кодирования.