**About Me:**I am a proficient data scientist and machine learning enthusiast with expertise in Python and SQL. My technical arsenal includes a deep understanding of machine learning algorithms, data structures, and algorithms, bolstered by comprehensive experience in frameworks such as SkLearn, TensorFlow, and libraries like Pandas and NumPy. With a solid foundation in EDA and DBMS, I leverage tools like Anaconda, Jupyter Notebook, and PowerBi to extract meaningful insights from data.**Projects:**In my professional journey, I have spearheaded impactful projects that showcase my adeptness in data analysis and predictive modeling. Notably, I developed a robust fake news detection model during my internship, achieving an impressive accuracy of 97.90% on the test dataset. Additionally, my work on predicting box office revenue showcased my ability to handle complex datasets and implement advanced machine learning techniques such as Random Forest, resulting in superior predictive performance.**Academic & Achievements:**Beyond my professional engagements, I am deeply involved in academic and extracurricular pursuits. My research paper, published on IEEE, underscores my commitment to advancing knowledge in the field. Furthermore, I have honed my problem-solving skills through platforms like LeetCode and CodeChef, earning accolades such as a CodeChef Rating of 1434 and a 5-star rating on HackerRank's Problem Solving section. These achievements reflect my dedication to continuous learning and innovation in the realm of data science and machine learning.