Apr 2022 – Jun 2022 · 2 mos · India · Remote

• I completed a two-month internship where I gained hands-on experience in the Machine Learning domain, focusing on applying supervised learning algorithms and performing crucial data preprocessing tasks. During this time, I worked extensively on preparing data for analysis, which involved cleaning, normalizing, and conducting feature engineering to enhance the quality of data used for model training. My work involved exploring and manipulating datasets using libraries such as NumPy and Pandas, which provided the necessary tools for efficient data handling.
• For data visualization and insights, I employed Seaborn and Matplotlib, creating meaningful plots and graphs to understand trends and patterns in the data. My experience also included training various models using Scikit-learn, applying algorithms to real-world datasets and evaluating their performance. Throughout the internship, I was responsible for implementing workflows that enhanced the models' predictive accuracy, ensuring the data was optimized for machine learning purposes. This experience solidified my understanding of the machine learning pipeline, from data preparation to model evaluation, using popular Python libraries to build, visualize, and improve models.