ROLE OF NLP IN MODERN CONTEXT
Presented by
 Immanuel Thomas Francis (221210050)
 Ishan Bhagat (221210051)
 Jainendra Kumar Verma (221210052)
 Jangala Ram Sai Chaitanya (221210053)
 Jugnu Gupta (221210054)
 Kapadia Dev Shailesh Kumar (221210055)
 Kartik Mittal (221210056)
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ISHAN
IMMANUEL
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JAINENDRA VERMA
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Introduction to NLP
Natural language processing is a field of
artificial intelligence that focuses on
enabling computers to understand,
interpret, and generate human languages.
History: NLP has come a long way
since its inception in the 1950s, with
significant advancements in the past decade
thanks to the use of deep learning and
neural networks.
Applications of NLP

Chatbots and virtual assistants: NLP allows for natural and seamless
communication with virtual assistants like Apple's Siri or Amazon's Alexa.

Sentiment analysis: NLP enables businesses to analyze customer sentiment
from social media posts, reviews, and other sources, in order to understand and
improve the customer experience.

Language translation: Services like Google Translate rely on NLP to accurately
translate text and speech between languages.

Information extraction: NLP can extract structured data from unstructured
sources, such as extracting information from a resume or a medical record.

Text classification and summarization: NLP can classify text into predefined
categories and summarize long documents into shorter, more digestible
versions.
NLP in Action
Examples of NLP in use include chatbots responding to customer
inquiries, language translation apps, and social media monitoring
tools that analyze customer sentiment.
Smart assistants like Apple’s Siri and Amazon’s Alexa recognize
patterns in speech thanks to voice recognition, then infer meaning
and provide a useful response.
How does Siri work?
1.
When your order Siri to perform an action, it records the
frequencies and soundwaves from your voice and converts them
into a code.
Siri then breaks down the code in context to identify patterns and
keywords.
3. This data gets input into an algorithm and is then matched against
thousands of combination of sentences to identify what your
phrase means.
4. The algorithm then determines the context of your sentence
through working around various literary expressions.
5. When Siri understands your request, it begins to assess the tasks
that need to be performed
2.
Challenges in NLP
Ambiguity and context dependence: Language is full of
ambiguity and can be heavily influenced by context, making it
difficult for computers to accurately understand it.
Idioms, slang, and figurative language: These can be particularly
difficult for computers to understand, as they often don't follow
the literal meanings of words.
Training data: In order for NLP models to be effective, they
require large amounts of labeled data to learn from, which can be
time-consuming and costly to obtain.
Advancements in NLP
Deep learning and neural networks: These have greatly improved
the accuracy and efficiency of NLP models.
Pre-trained language models: Models like BERT and GPT-3 have
set new benchmarks for NLP performance and have been widely
adopted in a variety of applications.
Ethical Considerations in NLP
Bias: NLP models can reflect the biases present in their
training data, leading to unfair and biased outcomes. It is
important to be aware of this and take steps to mitigate bias in
NLP models.
Transparency: It is important for NLP systems to be
transparent in their operation and decision-making processes,
in order to build trust with users and ensure responsible use.
Future of NLP
Continued development of
pre-trained language models
and other state-of-the-art
NLP techniques. Increasing
use of NLP in
personalization and
recommendation systems.
Potential for NLP to be used
in areas like healthcare and
education.
Video by sparkcognition
Conclusion
NLP has come a long way and has a wide range of applications
in the modern world. It is important to consider the ethical
implications of NLP and strive for responsible and transparent
use. The future of NLP looks promising, with exciting
developments on the horizon.