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Average Ratings 0 Ratings

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features
design
support

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Description

HumanFirst revolutionizes the way you handle infrastructure and workflows for exploring, curating, and scaling your AI training data. Our solutions empower the expansion of NLU and NLP capabilities, significantly speeding up the advancement of conversational AI. By ensuring that authentic voice-of-the-customer data is consistently integrated, we enhance the relevance and effectiveness of your models. With HumanFirst Studio, managing voice and text data for training and refining natural language understanding (NLU) models becomes effortless. Eliminate expensive and inconsistent data ingestion and labeling procedures, opting instead for a streamlined experience that enables immediate enhancements to your AI performance using actual data. You can easily import requests from your Search and Help Center, emails, live chat, or voice call logs to ensure your AI continually learns to understand customer needs better. This allows for the discovery of intents and their enhancement in precision. The traditional approach of guessing which intents require training and manually creating training phrases can be cumbersome, often resulting in insufficient coverage and accuracy of intents, which can hinder the overall effectiveness of your AI solutions. Ultimately, embracing HumanFirst allows your organization to focus on what truly matters: delivering exceptional customer experiences driven by intelligent AI.

Description

TextBlob is a Python library designed for handling textual data, providing an intuitive API to carry out various natural language processing functions such as part-of-speech tagging, sentiment analysis, noun phrase extraction, and classification tasks. Built on the foundations of NLTK and Pattern, it integrates seamlessly with both libraries. Notable features encompass tokenization (the division of text into words and sentences), frequency analysis of words and phrases, parsing capabilities, n-grams, and word inflection (both pluralization and singularization), alongside lemmatization, spelling correction, and integration with WordNet. TextBlob is compatible with Python versions 2.7 and higher, as well as 3.5 and above. The library is actively maintained on GitHub and is released under the MIT License. For users seeking guidance, thorough documentation is readily accessible, including a quick start guide and a variety of tutorials to facilitate the implementation of different NLP tasks. This rich resource equips developers with the tools necessary to enhance their text processing capabilities.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

NLTK No 
Python No 

Integrations

NLTK Yes 
Python Yes 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

HumanFirst.ai

Founded

2017

Country

Canada

Website

www.humanfirst.ai/

Vendor Details

Company Name

TextBlob

Country

United States

Website

textblob.readthedocs.io/en/dev/

Product Features

Conversational AI

Code-free Development No 
Contextual Guidance No 
For Developers No 
Intent Recognition No 
Multi-Languages No 
Omni-Channel No 
On-Screen Chats No 
Pre-configured Bot No 
Reusable Components No 
Sentiment Analysis No 
Speech Recognition No 
Speech Synthesis No 
Virtual Assistant No 

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Natural Language Processing

Co-Reference Resolution No 
In-Database Text Analytics No 
Named Entity Recognition No 
Natural Language Generation (NLG) No 
Open Source Integrations No 
Parsing No 
Part-of-Speech Tagging No 
Sentence Segmentation No 
Stemming/Lemmatization No 
Tokenization No 

Product Features

Natural Language Processing

Co-Reference Resolution No 
In-Database Text Analytics No 
Named Entity Recognition No 
Natural Language Generation (NLG) No 
Open Source Integrations No 
Parsing No 
Part-of-Speech Tagging No 
Sentence Segmentation No 
Stemming/Lemmatization No 
Tokenization No 

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