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If you are active in the AI space, then you must be familiar with NLP, which stands for Natural Language Processing. NLP is changing how machines can interact with and understand human language. This is a huge deal, especially in regions like India, where there are 20+ official languages and 19,000+ dialects. By leveraging NLP, […]
Data science powers decision-making across modern businesses, from data preparation and automation to advanced analytics and machine learning. Learning it requires a strong foundation in mathematics, statistics, programming, and practical problem-solving. The good news is that data science can be self-learned with the right resources and consistent practice. Books remain one of the most effective
The internet has become a massive, always-on focus group. Customers share opinions in product reviews, app store comments, support chats, social media posts, and community forums—often switching between languages and dialects in a single conversation. If you only analyze English, you’re ignoring a huge portion of what your customers actually feel. Recent estimates suggest roughly
Multilingual Sentiment Analysis – Importance, Methodology, and Challenges Read More »
There’s been a lot of talk about GPT-3 and generative AI in the news, social media, and probably from every AI practitioner or vendor whom you’ve been speaking with lately. Everyone is super excited about the future that such AI tools hold. But what exactly is this AI technology specifically and what does it mean
GPT-3: What is GPT-3 and what can it do for your business? Read More »
We’ve all heard of sentiment analysis, but what exactly is it and what can it do for your brand, your business, and how can you get started with it? Table Of Contents What is Sentiment Analysis?Why is Sentiment Analysis Important in Business?How are Businesses Using Sentiment Analysis? (Real-World Examples)How to Get Started with Sentiment AnalysisKeep
How Sentiment Analysis Keeps Your Brand in Check (and How to Get Started) Read More »
This is no new information or statistic that over 80% of the healthcare data available for stakeholders is unstructured. The rise of EHRs has exponentially made it easier for healthcare professionals to access, store, and modify interoperable data for their purposes. To give you a brief example of the different types of unstructured data available
Extracting Key Clinical Information from Electronic Health Records (EHRs) using NLP Read More »
Radiologists today face an overwhelming workload, spending hours reading and interpreting thousands of narrative medical imaging reports. With rising demand, manual reporting often leads to delays, inconsistencies, and missed findings. Natural Language Processing (NLP) is emerging as a transformative technology in healthcare, helping radiologists automate report extraction, improve diagnostic accuracy, and enhance patient outcomes. In
NLP in Radiology: Applications, Benefits & Challenges in Medical Imaging Reports Read More »
Language is complex—and so are the technologies we built to understand it. At the intersection of AI buzzwords, you’ll often see NLP and LLMs mentioned as if they’re the same thing. In reality, NLP is the umbrella methodology, while LLMs are one powerful tool under that umbrella. Let’s break it down human-style, with analogies, quotes,
NLP vs LLM: Differences Between Two Related Concepts Read More »
NLP datasets are the backbone of many natural language processing projects, offering flexibility for a wide range of tasks such as text classification, sentiment analysis, and question answering. The Blog Authorship Corpus, for instance, contains over 681,000 blog posts from nearly 20,000 bloggers, making it a rich resource for studying writing styles, author identification, and
Top NLP Dataset to Supercharge Your Machine Learning Models Read More »
Discover our NLP infographic: Learn how it works, explore benefits, challenges, market growth, use cases, and future trends in Natural Language Processing.
What is NLP? How it Works, Benefits, Challenges, Examples Read More »
