My passion lies in software development, with a strong inclination towards Machine Learning, Deep Learning, Robotics, and Game-Development using JavaScript. I consider my main language to be Java.
You can check my work by visiting my github profile.
Hello there! I am a passionate software developer with expertise in Java, Machine Learning, Deep Learning, and a touch of JavaScript.
My experience in Java has provided me with a solid foundation to build robust and efficient applications. The realms of Machine Learning and Deep Learning have captivated me with their limitless potential, driving me to explore cutting-edge algorithms and techniques to extract meaningful insights from data.
Beyond my professional endeavors, there’s another side to me – the game developer! As an avid gamer myself, I have delved into the world of game development, shaping my dreams and imagination into captivating virtual experiences.
About MeHere, I designed a model for predicting the words that can come after a word is typed. This model automatically checks the vocabulary and pronunciation and predict the next occurring word that can be suitable in the sentence. I also designed a model that analyse which country has more terror attacks. I have also worked on model that analyse the handwritten characters and recongnize them during my internship which trains itself, hence predict the characters.
During my data science internship, I gained proficiency in TensorFlow with Keras and utilized tokenizer, Python, Jupyter Notebook, NumPy, and Pandas to create powerful machine learning models. It was a fantastic learning experience, enabling me to make meaningful contributions to the field.
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A Java OOPS based 2 Player game where a Ninja fights with the army of Bad Dudes.
Technologies used : Java, Eclipse, OOPS, External Jars.
Case Study
The game challenges players to guess a hidden five-letter word by making consecutive guesses and receiving feedback on their progress.
Technologies used : JavaScript, HTML, CSS, npm, Rapid-API.
Case StudyLet Sentisonics analyze your emotions and curate Spotify playlists that match your mood instantly. Elevate your music experience with Sentisonics' intelligent mood detection and personalized soundtracks.
Technologies used : Python, Jupyter NoteBook, Spotipy, Tensorflow with Keras, OpenCV.
Case Study
In an ever-evolving world of finance, accurately predicting stock market movements has long been an elusive goal for investors and traders alike. While countless strategies and models have emerged over the years, one approach has recently gained significant traction due to its ability to capture complex patterns...
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