Projects
As a Machine Learning Engineering student, hands-on projects are vital for bridging theoretical knowledge and real-world applications. Machine learning is revolutionizing industries through data-driven decision-making. By working on projects, students gain practical experience in designing and deploying models using frameworks like TensorFlow and PyTorch, equipping them to tackle complex problems and contribute to innovative solutions.
Sentiment Analysis Using Logistic Regression
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Tech Stack : Python,Pandas,Numpy
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Description : Sentiment Analysis is a natural language processing (NLP) task that involves determining the emotional tone behind a body of text. This can range from positive and negative sentiments to neutral expressions. Logistic Regression is a statistical method commonly used for binary classification problems, making it suitable for sentiment analysis where the goal is to classify text as either positive or negative.
College Placement Prediction
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Tech Stack : Matplotlib,TensorFlow,Scikit-learning
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Description : The College Placement Prediction project aims to predict students' placement chances based on various factors, including academic performance, skills, and extracurricular activities. The project begins with data collection, gathering historical placement data from college records, which includes student profiles, academic scores, and placement outcomes.
Gym Fitness Website
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Tech Stack : HTML,CSS,Javascript
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Description : The Gym Fitness Website serves as an online platform to promote fitness services, provide information about gym facilities, and encourage potential members to join. The website is designed to be visually appealing and user-friendly, ensuring that visitors can easily navigate through the various sections to find the information they need. Utilizing HTML for structure and CSS for styling, the website aims to create an engaging experience for users.
