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The Hybrid Movie Recommender is a system that recommends movies using a combination of collaborative and content-based filtering techniques. The system is designed to address the cold start problem(new users) by using a popularity based approach. The dataset used for the system is obtained from Kaggle.

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hybrid_movie_recommendation's Introduction

Hi there I'm Daniel 👋

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Hi there, I'm a tech-savvy BTech student seeking a internship!

Welcome to my Github page! I'm a passionate and motivated student at PESU College, Bangalore, eager to enhance my skills and gain hands-on experience in the field of technology. As a quick learner and a problem solver, I believe in taking calculated risks to achieve my goals and create impactful projects.

At heart, I'm a team player who thrives in a collaborative environment. I'm always excited to work with like-minded individuals who are passionate about technology and share a common goal of creating innovative solutions that make a difference.

I'm eager to find an internship opportunity where I can apply my skills and knowledge to work on impactful projects. Whether it's software development, data analysis,Database Management Systems or machine learning, I'm ready to roll up my sleeves and dive in.

My Github page is a testament to my skills and interests. You'll find a variety of projects that demonstrate my ability to code in languages such as Python,Java,C++, Javascript,PHP,MySQL and C. I've worked on projects ranging from building websites to creating machine learning models and analyzing data.

I'm excited to join a team where I can contribute my skills, learn new things, and make an impact in the field. So if you're looking for a motivated and skilled intern who's ready to take on new challenges, please don't hesitate to get in touch. Let's create something awesome together!