What is BERT?

BERT stands out as a crucial language model that employs a method for pre-training language representations. This initial pre-training stage encompasses extensive exposure to large text corpora, such as Wikipedia and other diverse sources. Once this foundational training is complete, the knowledge acquired can be applied to a wide array of Natural Language Processing (NLP) tasks, including question answering, sentiment analysis, and more. Utilizing BERT in conjunction with AI Platform Training enables the development of various NLP models in a highly efficient manner, often taking as little as thirty minutes. This efficiency and versatility render BERT an invaluable resource for swiftly responding to a multitude of language processing needs. Its adaptability allows developers to explore new NLP solutions in a fraction of the time traditionally required.

Pricing

Price Starts At:
Free
Free Version:
Free Version available.

Integrations

All BERT Integrations
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Screenshots and Video

BERT Screenshot 1
BERT Screenshot 1

Company Facts

Company Name:
Google
Date Founded:
1998
Company Location:
United States
Company Website:
cloud.google.com/ai-platform/training/docs/algorithms/bert-start

Product Details

Deployment
SaaS
Training Options
Documentation Hub

Product Details

Target Company Sizes
Individual
1-10
11-50
51-200
201-500
501-1000
1001-5000
5001-10000
10001+
Target Organization Types
Mid Size Business
Small Business
Enterprise
Freelance
Nonprofit
Government
Startup
Supported Languages
English

BERT Categories and Features

Natural Language Processing Software

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

Large Language Models

Embedding Models

AI Models

More BERT Categories

BERT Customer Reviews

Write a Review
  • Reviewer Name: A Verified Reviewer
    Position: Backend Developer
    Has used product for: Less than 6 months
    Uses the product: Monthly
    Org Size (# of Employees): 100 - 499
    Feature Set
    Layout
    Ease Of Use
    Cost
    Customer Service
    Would you Recommend to Others?
    1 2 3 4 5 6 7 8 9 10

    BERT Implementation

    Date: Aug 27 2024
    Summary

    BERT provided results with high accuracy. BERT allowed flexibility to cdeo and handle edge cases better.

    Positive

    When BERT model implemented on stress detection use case, BERT as it handles context of the text was easily able to identify negation sentence like detecting "I am NOT happy" as a stressful text which was not happening in other models like logistic regression, decision tree, random forest, multinomial naive bayes, CNN, RNN, LSTM etc.

    Negative

    difficulty in finding a suitable multilingual datastet to train the model for both hind and english use cases.

    Read More...
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