Page 399 - AI Ver 3.0 class 10_Flipbook
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UNIT 6.2
NATURAL LANGUAGE
PROCESSING (PRACTICAL)
Learning Outcomes
• No-Code NLP Tools • Natural Language Processing: Use Case
• Sentiment Analysis • NLP with Orange Data Mining Tool
Natural Language Processing (NLP) helps computers understand and process human language. It powers tools like
voice assistants and chatbots. No-code AI tools make NLP accessible to everyone, even without coding knowledge.
These tools allow users to perform tasks like sentiment analysis and topic identification through simple visual
interfaces.
No-Code NLP Tools
No-code NLP tools enable users to perform Natural Language Processing tasks without programming knowledge.
Different platforms offer intuitive interfaces for text mining, sentiment detection, and more. These tools are ideal
for businesses and individuals seeking quick and scalable NLP solutions.
Orange Data Mining is an open-source, no-code/low-code data visualisation and analysis tool that enables users
to perform machine learning, data mining, and predictive modelling without coding. It provides a user-friendly,
drag-and-drop interface that simplifies data analysis workflows.
MonkeyLearn is an easy-to-use, no-code NLP platform that makes text analysis accessible to businesses and
non-technical users. Whether you need sentiment analysis, keyword extraction, or customer feedback analysis,
MonkeyLearn provides a powerful and automated solution for text-based insights.
MeaningCloud is a No-Code Natural Language Processing (NLP) tool that provides text analytics services.
It allows users to extract meaningful insights from text data without requiring programming knowledge. It
offers APIs that can be integrated into applications, but it also provides a no-code platform where users can
upload text and get insights without programming.
Brainy Fact
Raúl Garreta is the founder and former CEO of MonkeyLearn. He also co-founded Tryolabs in 2009, a company
that helped businesses in the U.S. build AI-powered products.
Natural Language Processing (Practical) 397

