These are the skills I have acquired; while I have proficiency in various other areas, these are the primary ones in which I am fluent.
I have a strong background in machine learning and have worked on projects such as a language translation tool, sentiment analysis, gender prediction, plot prediction, and many more.
In my capacity as a Java Programmer at CodSoft, I've effectively executed three comprehensive projects, highlighting my expertise in Java, Swing, and MySQL. Proficient in crafting user-friendly GUIs, I leverage tools such as Apache NetBeans and IntelliJ IDEA to ensure efficient and effective development.
My proficiency extends to HTML, CSS, and JavaScript, allowing me to comprehend and write prebuilt code effectively. I have successfully developed my portfolio from scratch. Additionally, for SIH23, I created two websites—an Aadhaar card website and a service website—to test machine learning models.
I am familiar with Python libraries such as Matplotlib, Scikit-Learn, Pandas, NumPy, Seaborn, and more. In addition to that, I have proficiency in tools like Excel and Power BI. My knowledge of SQL enables me to perform tasks such as data visualization, cleaning, and plotting
The language translator tool was built using NLP (Natural Language Processing), machine learning, and basic concepts of deep learning. It leveraged transformers, Hugging Face, and dataset libraries. Through effective data cleaning and management, a robust language translator was developed, capable of translating English to Hindi.
The Sentiment Analysis project was designed to analyze and understand the sentiments expressed in textual data. This project leverages Natural Language Processing (NLP) techniques and machine learning algorithms to determine the emotional tone of a given piece of text. The primary goal is to classify the sentiment of the text into categories such as positive, negative, or neutral.
The Age and Gender Predictor model is a powerful machine learning application designed to predict the age and gender of individuals based on facial features. Utilizing advanced algorithms and a trained neural network, the model takes input images and quickly provides accurate predictions. The user interface is simple, allowing users to easily input images for analysis. The model's potential applications include marketing, customer analytics, and security. Continuous updates focus on improving accuracy, and ethical considerations regarding privacy are paramount in the model's development and implementation.
The Plot Price Prediction project aims to forecast the prices of plots in Bangalore using machine learning techniques. By leveraging historical data and relevant features, this project aims to create a predictive model that estimates the price of real estate plots in Bangalore.
The provided Python script utilizes Streamlit to create a Movie Recommender System. Users select a movie from a dropdown, click the "Show Recommendations" button, and receive a list of recommended movies based on similarity. Movie data and similarity matrices are loaded from pickled files, and movie posters are fetched from "https://www.themoviedb.org/". The recommendations include movie titles and posters, presented in a responsive layout. Custom CSS styling enhances the Streamlit app's appearance, featuring a green-themed button and a light background color.
Experienced professional with a strong background in machine learning and software development. As a Machine
Learning Contributor and Frontend Developer at Smart India Hackathon 2023, I led the development of a dynamic
translation model integrated into a website through an API. In my role as a Java Programmer at CodSoft, I've
successfully executed three comprehensive projects, showcasing expertise in Java, Swing, and MySQL. Proficient
in designing user-friendly GUIs using tools like Apache NetBeans and IntelliJ IDEA. Committed to innovation
and excellence in every project.
Coding : Java , Data Structures and Algorithms , JavaScript, Python, Machine Learning, Data
Cleaning, Data Visualization (Tableau, Power BI), Deep Learning (TensorFlow, Keras), NLP, docker.
Databases : DBMS, Flask.
Web Dev : Html, css, JavaScript , Figma.
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