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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
aziende
Abbiamo dati su 72 aziende che usano Spark NLP. La nostra lista di clienti Spark NLP è disponibile per il download ed è arricchita con specifiche vitali dell'azienda, incluse classificazione industriale, dimensioni organizzative, posizione geografica, round di finanziamenti e cifre di ricavi, tra gli altri.
Azienda | Paese | Settore | Dipendenti | Entrate |
---|---|---|---|---|
Poshmark | Stati Uniti | Retail Apparel And Fashion | 2.7K | $353M |
![]() John Snow Labs | Stati Uniti | It Services And It Consulting | 91 | $7M |
![]() Lovelytics | Stati Uniti | Data Infrastructure And Analytics | 80 | |
CVS Health | Stati Uniti | Hospitals And Health Care | 300K | $331B |
![]() OLX Group | Paesi Bassi | It Services And It Consulting | 4.5K | $1.2B |
EXL Services | India | It Services And It Consulting | 1K | |
Databricks | Stati Uniti | Software Development | 8.8K | $600M |
Brainly | Polonia | Software Development | 820 | $14M |
Team Go | Stati Uniti | Advertising Services | 58 | |
Planned Systems International | Stati Uniti | It Services And It Consulting | 554 | |
NielsenIQ | Stati Uniti | Information Services | 30K | $4.9B |
SAILOG, LLC | Svizzera | Travel Arrangements | 20 | $4.8M |
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Spark NLP è utilizzata in 11 paesi
Ci sono 20 alternative a Spark NLP
Domande frequenti
I nostri dati provengono da offerte di lavoro raccolte da milioni di aziende. Monitoriamo queste offerte sui siti web delle aziende, sui portali di lavoro e su altre piattaforme di reclutamento. Analizzare le offerte di lavoro offre un metodo affidabile per comprendere le tecnologie impiegate dalle aziende, inclusi i loro strumenti interni.
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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.
Puoi accedere a un elenco aggiornato di aziende che utilizzano Spark NLP visitando TheirStack.com. La nostra piattaforma fornisce un database completo di aziende che utilizzano varie tecnologie e strumenti interni.
Fino ad ora, abbiamo dati su 72 aziende che utilizzano Spark NLP.
Spark NLP è utilizzato da una vasta gamma di organizzazioni in vari settori, inclusi "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". Per un elenco completo di tutti i settori che utilizzano Spark NLP, si prega di visitare TheirStack.com.
Alcune delle aziende che utilizzano Spark NLP includono Poshmark, John Snow Labs, Lovelytics, CVS Health, OLX Group, EXL Services, Databricks, Brainly, Team Go, Planned Systems International e molte altre. Puoi trovare un elenco completo di 72 aziende che utilizzano Spark NLP su TheirStack.com.
Secondo i nostri dati, Spark NLP è più popolare in Stati Uniti (37 companies), India (3 companies), Regno Unito (3 companies), Francia (2 companies), Polonia (2 companies), Svizzera (2 companies), Afghanistan (1 companies), Gabon (1 companies), Germania (1 companies), Giappone (1 companies). Tuttavia, è utilizzato da aziende in tutto il mondo.
Puoi trovare aziende che utilizzano Spark NLP cercandolo su TheirStack.com. Tracciamo le offerte di lavoro di milioni di aziende e le utilizziamo per scoprire quali tecnologie e strumenti interni stanno utilizzando.