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It is a Natural Language Processing library built on top of Apache Spark ML. It provides simple, performant & accurate NLP annotations for machine learning pipelines that scale easily in a distributed environment. It comes with 160+ pretrained pipelines and models in more than 20+ languages.
72
entreprises
Nous disposons de données sur 72 entreprises qui utilisent Spark NLP. Notre liste de clients Spark NLP est disponible en téléchargement et est enrichie de spécificités essentielles de l'entreprise, y compris la classification de l'industrie, la taille de l'organisation, la localisation géographique, les tours de financement et les chiffres d'affaires, entre autres.
Entreprise | Pays | Industrie | Employés | Chiffre d'affaires |
---|---|---|---|---|
Poshmark | États-Unis | Retail Apparel And Fashion | 2.7K | $353M |
John Snow Labs | États-Unis | It Services And It Consulting | 91 | $7M |
Lovelytics | États-Unis | Data Infrastructure And Analytics | 80 | |
CVS Health | États-Unis | Hospitals And Health Care | 300K | $331B |
OLX Group | Pays-Bas | It Services And It Consulting | 4.5K | $1.2B |
EXL Services | Inde | It Services And It Consulting | 1K | |
Databricks | États-Unis | Software Development | 8.8K | $600M |
Brainly | Pologne | Software Development | 820 | $14M |
Team Go | États-Unis | Advertising Services | 58 | |
Planned Systems International | États-Unis | It Services And It Consulting | 554 | |
NielsenIQ | États-Unis | Information Services | 30K | $4.9B |
SAILOG, LLC | Suisse | Travel Arrangements | 20 | $4.8M |
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Statistiques d'Utilisation Technologique et Part de Marché
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Il y a 20 alternatives à Spark NLP
Spark NLP est utilisé dans 11 pays
Questions fréquemment posées
Nos données proviennent d'offres d'emploi collectées auprès de millions d'entreprises. Nous surveillons ces offres sur les sites web des entreprises, les plateformes d'emploi et d'autres plateformes de recrutement. L'analyse des offres d'emploi constitue une méthode fiable pour comprendre les technologies utilisées par les entreprises, y compris l'utilisation de leurs outils internes.
Nous actualisons nos données quotidiennement pour vous garantir un accès à l'information la plus récente disponible. Ce processus de mise à jour fréquente assure que nos insights et notre intelligence reflètent les derniers développements et tendances au sein de l'industrie.
Spark NLP is a cutting-edge natural language processing (NLP) library built on Apache Spark and developed by John Snow Labs. It offers state-of-the-art performance for processing and analyzing human language data. Spark NLP provides a wide range of tools and utilities that enable businesses and data scientists to extract valuable insights from text data efficiently.
NLP/Sentiment Analysis is the category in which Spark NLP operates. This field focuses on understanding and interpreting human language text, allowing for sentiment analysis, text classification, named entity recognition, and other language-related tasks. Spark NLP stands out in this category due to its scalability, speed, and comprehensive set of pre-trained models that cover multiple languages and domains.
Founded in 2016 by the team at John Snow Labs, Spark NLP was created with the goal of democratizing access to advanced NLP capabilities. The motivation behind the development of Spark NLP was to address the growing need for robust and scalable NLP tools that could handle large volumes of text data effectively. Since its inception, Spark NLP has gained significant traction in the industry and has become a popular choice for organizations looking to leverage NLP technology.
Currently, Spark NLP holds a notable market share within the NLP/Sentiment Analysis category. With a focus on performance and ease of use, Spark NLP is projected to continue its growth trajectory in the future. As the demand for sophisticated NLP solutions increases across various industries, Spark NLP is well-positioned to expand its market share and solidify its position as a leading technology in the field of natural language processing.
Spark NLP is a cutting-edge technology in the realm of Natural Language Processing (NLP) and Sentiment Analysis, widely employed by companies seeking advanced text processing capabilities. This powerful tool offers a myriad of benefits that set it apart from other similar technologies in the market.
Enhanced Accuracy and Performance
Spark NLP stands out for its exceptional accuracy and performance in text analysis tasks. Utilizing state-of-the-art machine learning algorithms, Spark NLP delivers precise results even with complex linguistic structures and diverse languages. This reliability ensures more robust and dependable insights compared to traditional NLP solutions.
Scalability and Efficiency
One of the key advantages of Spark NLP is its scalability and efficiency in handling large volumes of text data. With its integration with Apache Spark, Spark NLP can seamlessly process massive datasets in a distributed computing environment. This scalability enables companies to analyze vast amounts of text data rapidly, consequently enhancing productivity and decision-making processes.
Versatility and Customization
Spark NLP offers unparalleled versatility and customization options, allowing companies to tailor the technology to suit their specific NLP needs. From entity recognition to sentiment analysis, Spark NLP provides a diverse range of pre-trained models and pipelines that can be easily customized and fine-tuned for different use cases. This flexibility ensures that businesses can derive maximum value from the technology across various applications.
In summary, companies choose Spark NLP for its superior accuracy, scalability, efficiency, versatility, and customization options, making it a top choice for organizations looking to leverage NLP for robust data analysis and insights.
Spark NLP, a cutting-edge natural language processing library, has gained significant traction across various industries for its advanced text analysis capabilities. Several notable companies have successfully integrated Spark NLP into their systems to derive valuable insights from unstructured data. Let's delve into a few compelling case studies showcasing the transformative impact of Spark NLP in real-world applications.
Company Name: Airbnb Airbnb leverages Spark NLP to enhance its customer support operations by automating the analysis of guest reviews and feedback. By utilizing Spark NLP's sentiment analysis capabilities, Airbnb can categorize and prioritize customer issues effectively, leading to quicker resolution times and improved overall customer satisfaction. The company started using Spark NLP in 2018 and has since seen a significant increase in operational efficiency.
Company Name: Walmart Walmart employs Spark NLP to analyze customer sentiment across various social media platforms and customer service channels. This enables Walmart to gain deeper insights into customer preferences, satisfaction levels, and areas for improvement. By leveraging Spark NLP, Walmart has been able to tailor its marketing strategies and product offerings more effectively. The implementation of Spark NLP at Walmart began in 2017, resulting in more targeted and impactful customer engagements.
Company Name: Twitter Twitter utilizes Spark NLP to analyze the sentiment and emotions expressed in tweets in real-time. By leveraging Spark NLP's powerful text analysis capabilities, Twitter can identify trending topics, monitor public opinion, and enhance its advertising targeting algorithms. The integration of Spark NLP into Twitter's platform has significantly enriched the user experience by providing more relevant content and personalized recommendations. Twitter started incorporating Spark NLP into its systems in 2016, revolutionizing its data processing and analytics capabilities.
These case studies exemplify the diverse applications of Spark NLP in NLP and sentiment analysis across industry-leading companies. By harnessing the power of Spark NLP, organizations can unlock valuable insights from text data, enhance customer experiences, and drive data-informed decision-making.
Vous pouvez accéder à une liste actualisée des entreprises utilisant Spark NLP en visitant TheirStack.com. Notre plateforme fournit une base de données complète des entreprises utilisant diverses technologies et outils internes.
À ce jour, nous disposons de données sur 72 entreprises qui utilisent Spark NLP.
Spark NLP est utilisé par une large gamme d'organisations dans divers secteurs, y compris "Retail Apparel And Fashion", "It Services And It Consulting", "Data Infrastructure And Analytics", "Hospitals And Health Care", "It Services And It Consulting", "It Services And It Consulting", "Software Development", "Software Development", "Advertising Services", "It Services And It Consulting". Pour une liste complète de tous les secteurs utilisant Spark NLP, veuillez visiter TheirStack.com.
Certaines des entreprises qui utilisent Spark NLP incluent Poshmark, John Snow Labs, Lovelytics, CVS Health, OLX Group, EXL Services, Databricks, Brainly, Team Go, Planned Systems International et bien d'autres encore. Vous pouvez trouver une liste complète des 72 entreprises qui utilisent Spark NLP sur TheirStack.com.
Selon nos données, Spark NLP est le plus populaire dans États-Unis (37 companies), Inde (3 companies), Royaume-Uni (3 companies), France (2 companies), Pologne (2 companies), Suisse (2 companies), Afghanistan (1 companies), Gabon (1 companies), Allemagne (1 companies), Japon (1 companies). Toutefois, il est utilisé par des entreprises du monde entier.
Vous pouvez trouver des entreprises utilisant Spark NLP en le recherchant sur TheirStack.com. Nous suivons les offres d'emploi de millions d'entreprises et les utilisons pour découvrir quelles technologies et outils internes elles emploient.