RISHABH VYAS

Optimized machine learning models for regression, classification, and clustering, leveraging advanced data wrangling techniques to handle missing values and outliers, and applying feature engineering methods to enhance model performance. Executed noteworthy NLP, computer vision, and financial time series projects, achieving 5-10% higher accuracy than benchmarks. Proficiently trained various Machine Learning and Deep Learning models, including ANNs, CNNs, RNNs, and LSTM, implementing transfer learning for 15% efficiency boost. Conducted data analysis with pandas, delivering valuable insights for data-driven decisions and improved project outcomes.

Gained practical expertise in regression and classification algorithms, applying decision trees, support vector machines, and deep learning models (CNNs) to real-world datasets. Implemented data preprocessing techniques such as text cleaning and image augmentation, contributing to improved model performance. Strengthened problem-solving skills by tackling complex machine learning challenges and experimenting with various hyperparameters to optimize model performance. Collaborated with a team to conduct model evaluation and fine-tuning, resulting in a 5% increase in classification accuracy for a medical image classification project.