Machine Learning involves the development of algorithms and models that enable computers to learn patterns and make predictions or decisions without being explicitly programmed
Experienced technologist with 500+ deployed microservices for image and text processing, including facial recognition, Diabetic Retinopathy detection, and NLU-based chatbots.
Machine Learning involves the development of algorithms and models that enable computers to learn patterns and make predictions or decisions without being explicitly programmed
Deep Learning is a subset of machine learning that focuses on neural networks with multiple layers, allowing models to automatically learn hierarchical representations of data.
HTML5 (Hypertext Markup Language) is the latest markup language for web pages, and CSS (Cascading Style Sheets) styles and formats their visual presentation.
Data Analytics is the process of examining, cleaning, transforming, and modeling data to extract useful information, draw conclusions, and support decision-making.
Python is a versatile, high-level programming language known for its readability and simplicity, widely used in web development, data science, machine learning, and more.
ReactJS is a JavaScript library for building user interfaces, particularly single-page applications where components update efficiently, providing a more dynamic and responsive user experience.
R is a programming language and environment commonly used for statistical computing and graphics, popular among statisticians and data scientists.
SQL (Structured Query Language) is a domain-specific language for managing and manipulating relational databases, used for tasks such as querying, updating, and modifying data.
Amazon Web Services (AWS) is a versatile cloud platform, offering computing, storage, machine learning, analytics, and more for scalable and flexible solutions
C++ is a powerful, general-purpose programming language known for its efficiency and versatility & Go is a statically-typed programming language developed by Google, designed for simplicity and efficiency.
Brain Tumor Classification using DenseNet and ResNet, this project involves medical image analysis for brain tumor classification, a critical application in healthcare
Melanoma classification is important for early detection of skin cancer, and the use of deep learning models like AlexNet and DenseNet can enhance accuracy
Pneumonia Classification Using Chest X-Ray with Probabilistic Neural Network and VGG19 is a significant medical application, by using it we can contribute to accurate diagnosis
Chatbot for college admissions has practical applications in improving user experience and efficiency in the college admissions process.
Resume sorting based on Job Description is an automated resume sorting that can greatly assist in the recruitment process, making it more efficient and unbiased.Using Bert model
Fake news detection using LSTM: With the proliferation of misinformation, fake news detection using LSTM can contribute to more reliable information dissemination.
Uniting Natural Language Understanding (NLU) for FAQ response and a Question-Answer System leveraging BIADF and DCN from unstructured data, this project creates an Integrated Cognitive Assistant
This web application aims to connect manufacturers and contractors. Contractors can submit their requirements, and the AI will generate quotations based on the manufacturer's product range.
AI Proctoring Tool: Utilizes advanced algorithms for real-time monitoring, ensuring exam integrity and preventing cheating in online assessments. Enhances credibility, providing a secure environment for remote education
Compressive strength of Concrete predictions using GRU. Predicting compressive strength can help optimize concrete mixtures for better performance..
Crossword Project: Appeals to puzzle enthusiasts, introducing a novel use of BERT in natural language processing for crossword solving. Engages a non-technical audience with a unique application of NLP.
I completed my postgraduate in Communication Systems. I did face recognition system on occluded images using a Convolutional neural network and achieved 98.3% accuracy. I published 3 papers in the IEEE digital library during my post-graduation and achieved "best paper" and "best all-rounder of the year" awards.
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Design and develop the AI microservices for the NLU based SAAS product and maintain the AWS infrastructure for the deployment of the product. Contribute to the development of UI for the application using ReactJS. Create a meaningful dashboard for the customer to get insights about the performance of the chatbot.
Analyze user needs and software requirements to determine the feasibility of design within time and cost constraints. Design, develop, and modify software systems, using scientific analysis and mathematical models to predict and measure outcome and consequences of design.
Conduct research in a particular field of knowledge and publish findings in professional journals, books, or electronic media. Prepare and deliver lectures to undergraduate or graduate students on topics such as DSP, AI, and Image processing
Conduct research in a particular field of knowledge and publish findings in professional journals, books, or electronic media. Prepare and deliver lectures to undergraduate or graduate students on topics such as DSP, AI, and Image processing
A detailed tutorial on implementing time-series forecasting with Gated Recurrent Units (GRU) in Python, using the Airline Passenger Dataset to demonstrate how to build, train, and visualize a predictive model for sequential data.
A comprehensive tutorial on building a text generation model using Long Short-Term Memory (LSTM) networks in TensorFlow and Keras, explaining the process from data preparation to generating new text sequences.
A practical walkthrough of implementing Long Short-Term Memory (LSTM) networks using R and Keras, demonstrating how to build, train, and evaluate LSTM models for handling sequential data and complex machine learning tasks.