I am a dedicated aspiring developer transitioning into AI, Full-Stack development, and Bioinformatics, focusing on building modern solutions with JavaScript and machine learning.
As a motivated Computer Science and Engineering student specializing in Artificial Intelligence at Amrita Vishwa Vidyapeetham, I am passionate about leveraging technology to drive innovation and solve complex problems. With a strong foundation in web development, I possess a solid understanding of front-end technologies and frameworks. Throughout my academic journey, I have acquired a diverse skill set encompassing programming languages, data structures, and algorithms. I have actively engaged in projects and coursework focused on machine learning, natural language processing, and computer vision, allowing me to explore the fascinating applications of AI. Driven by a continuous desire for learning and growth, I am committed to staying updated with the latest industry trends and emerging technologies. I am particularly excited about applying my knowledge of AI and web development to create intelligent and user-friendly web applications. Apart from my technical pursuits, I am a proactive team player and possess strong communication skills. I enjoy collaborating with like-minded individuals to achieve shared goals and contribute to a positive work environment. I am open to exploring internship opportunities, projects, and collaborations that allow me to apply my skills in web development and AI. Feel free to connect with me to discuss potential opportunities or share insights within the tech community. Let's connect and together create a future where technology empowers and enhances our lives."
Python, R, HTML, CSS, JavaScript React Js, Next Js
B.Tech in Computer Science, Amrita Vishwa Vidyapeetham
Built more than 25 projects
Full stack development refers to the practice of working on both the front-end (client-side) and back-end (server-side) of an application. A full stack developer has the skills to build a complete project from the user interface to the database and server logic.
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Deep learning is a sophisticated subset of machine learning that utilizes multi-layered artificial neural networks to autonomously identify complex patterns within massive datasets.
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Machine learning is a subset of artificial intelligence that focuses on building systems that learn from data to improve their performance on a specific task over time, rather than being explicitly programmed for every outcome.
Read moreAI framework that improves Large Language Model (LLM) accuracy by retrieving data from external, trusted knowledge sources (like databases or documents) to ground its responses
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Bioinformatics is the interdisciplinary field that develops methods and software tools for understanding biological data, especially when the data sets are large and complex.
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Reinforcement learning is an area of machine learning where an agent learns to make decisions by performing actions in an environment to maximize a cumulative reward through trial and error.
Read moreReinforcement learning is an area of machine learning where an agent learns to make decisions by performing actions in an environment to maximize a cumulative reward through trial and error.
Read moreReinforcement learning is an area of machine learning where an agent learns to make decisions by performing actions in an environment to maximize a cumulative reward through trial and error.
Read moreWelcome to my work portfolio! Explore a collection of projects showcasing my expertise in AI, Machine Learning and Deep Learning.
ML,Bigdata
Deep Learning, CNN, KNN, RNN
Signal Processing, Machine Learning
ML, BioInformatics
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