An Investigation into Deep Learning-Based Text Summarization Using Transformer Architecture: Training BART, PEGASUS, and T5 models on the CNN/Daily Mail Dataset and Implementing a Text Summarization API Based on the BART model using the Streamlit Library.
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Automatic speech recognition (ASR) converts a speech signal to text, mapping a sequence of audio inputs to text outputs. Finetune state-of-the-art deep learning model Wav2Vec2 on the speech recognition dataset MInDS-14 to transcribe audio to text.
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Sentiments analyzing App implemented with transformers and Streamlit. Finetuning DistilBERT - offers a lighter version of BERT; runs 60% faster while maintaining over 95% of BERT’s performance- for this project. The dataset used is IMBD dataset.
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This project employs an extractive question-answering approach, which entails answering questions based on a provided passage or document. The project involves training a BERT model on the Stanford Question Answering Dataset (SQuAD) to develop a robust question-answering system.
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Project for Translating Text from English to French. The aim of this project is to accurately convey the meaning and content of the original text while maintaining its cultural context, tone, and style. Fine tuning the model Helsinki NLP opus mt-en-fr on KDE4 dataset for this project.
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Implementing extractive text summarization using BERT and RoBERTa. Summarizing the given text by extracting the main content from the available text. For accomplishing this BERT and RoBERTa are fine tuned on cnn/daily mail dataset. ROUGE score is used to measure the accuracy of the trained model.
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This project involves the application of image processing and computer vision techniques to locate objects in images and draw bounding boxes around them. It includes fine-tuning the DETR (DEtection TRansformer) model on the CPPE-5 dataset. Object detection can be used in various applications, including object tracking in sports matches, object counting, autonomous driving, and image search.
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Implementing Explainable AI (XAI) with LIME: Using the XAI method LIME to provide explanations for machine learning prediction models, including Decision Trees, Random Forests, and AdaBoost. These models are utilized to predict wine quality based on various features. LIME produces insightful explanations for the results of these models.
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Diagnosing mental health issues based on symptoms and medication, analyzing the performance and accuracy of various classification algorithms such as Naive Bayes, SVM, Random Forest, and XGBoost, while also implementing various techniques to handle null values and address data imbalance.
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Coursework: Core Statistics, R Programming, Predictive Analytics with Python (Machine Learning, Deep Learning), Text Summarisation (NLP, Transformer Architecture, Git), Database Management (SQL), Big Data (Azure), Data Visualisation(Tableau), Data Mining
Coursework: Business Analytics, Statistical Analysis, Linear Models, Database Management
Coursework: Agile Methodologies, Problem Solving, Object Oriented Programming
Welcome to my corner of the internet! I'm a dedicated Data Science enthusiast armed with an advanced master's degree in Data Science and Analytics. I work as a technical writer on Medium.
While I don't have prior industrial experience, I have gained extensive experience through various data science projects. Many of my coursework assignments have involved working with real-world data to tackle practical problems.
Currently, I'm eager to apply everything I've learned at university and gain hands-on work experience.
As part of my project work, I developed a text summarizer using transformer architecture. This experience ignited my interest in Natural Language Processing (NLP), leading me to explore and develop various NLP models for different NLP tasks.
One of my favorite activities is translating data into meaningful conclusions and findings. I also have a keen interest in neuroscience and psychology, and I aspire to undertake projects that leverage NLP to solve problems in the psychological sector.
Outside of work, I'm passionate about traveling and photography. I take great pleasure in arranging and decorating my home and nurturing my collection of plants.
Feel free to peruse my articles, delve into my projects, and immerse yourself in the realm of Data Science and NLP. Let's embark on a quest for knowledge and innovation together!