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What is Spark NLP?

Explore the groundbreaking potential of large language models as they revolutionize Natural Language Processing (NLP) through Spark NLP, an open-source library that provides users with scalable LLMs. The entire codebase is available under the Apache 2.0 license, offering pre-trained models and detailed pipelines. As the only NLP library tailored specifically for Apache Spark, it has emerged as the most widely utilized solution in enterprise environments. Spark ML includes a diverse range of machine learning applications that rely on two key elements: estimators and transformers. Estimators have a mechanism to ensure that data is effectively secured and trained for designated tasks, whereas transformers are generally outcomes of the fitting process, allowing for alterations to the target dataset. These fundamental elements are closely woven into Spark NLP, promoting a fluid operational experience. Furthermore, pipelines act as a robust tool that combines several estimators and transformers into an integrated workflow, facilitating a series of interconnected changes throughout the machine-learning journey. This cohesive integration not only boosts the effectiveness of NLP operations but also streamlines the overall development process, making it more accessible for users. As a result, Spark NLP empowers organizations to harness the full potential of language models while simplifying the complexities often associated with machine learning.

What is DeepNLP?

SparkCognition, a leader in industrial artificial intelligence, has developed an innovative natural language processing solution designed to streamline the management of unstructured data in organizations, enabling employees to focus on critical business decisions. Their DeepNLP technology leverages machine learning to efficiently automate the processes of data retrieval, classification, and analysis. By seamlessly integrating into current workflows, DeepNLP empowers companies to swiftly adapt to evolving business environments and obtain prompt responses to targeted inquiries, enhancing overall operational efficiency. This capability not only saves time but also significantly improves the decision-making process across various sectors.

Media

Media

Integrations Supported

ALBERT
APIFuzzer
Apache Spark
BERT
Conda
ELMO
Facebook
Flair
Java
Maven
OpenAI
OpenAI Whisper
Python
R
RoBERTa
Scala
T5
TensorFlow
XLNet
spaCy

Integrations Supported

ALBERT
APIFuzzer
Apache Spark
BERT
Conda
ELMO
Facebook
Flair
Java
Maven
OpenAI
OpenAI Whisper
Python
R
RoBERTa
Scala
T5
TensorFlow
XLNet
spaCy

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

John Snow Labs

Company Location

United States

Company Website

sparknlp.org

Company Facts

Organization Name

SparkCognition

Date Founded

2013

Company Location

United States

Company Website

www.sparkcognition.com/products/deepnlp/

Categories and Features

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

Categories and Features

Data Extraction

Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

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