About

Prateek Agrawal is a highly skilled Machine Learning Engineer with over 5 years of experience in the field of Data Science and Machine Learning. He is currently working at Uber, where he is applying Causal Machine Learning to predict ride demand for multiple fare rounding strategies. Prateek is passionate about the power of data and loves to turn data into information and information into insight. Prateek's expertise lies in image classification, image detection, multi-task modeling, interpretation of deep learning models, and time series analysis. He has experience in running deep learning on cloud, mobile, and embedded platforms. Prateek has worked on various projects, including self-supervised learning for traffic light detection, driveable area detection, and depth perception from a mono camera for autonomous driving. Before joining Uber, Prateek worked as a System Engineer - Data Science at Infosys, where he integrated data from different data warehouses to build one large dataset. He wrote python scripts to implement constraint-based data cleaning and preprocessing, such as imputing missing values, removing correlated features, and data normalization. Prateek also automated feature selection to decrease the complexity of the dataset and optimize the training time. He built statistical models by analyzing the behavior and spending patterns of customers to take informed financial decisions. Prateek holds a Master's degree in Computer Science from the Illinois Institute of Technology and a Bachelor's degree in Computer Science from Dayananda Sagar University. He is proficient in ML, Deep Learning, Data Science, Research Science, AI, Supervised Learning, Mobile, XGBoost, Django, and Javascript. With 7.52 years of relevant experience, Prateek is a highly motivated and driven individual who is always looking for new challenges and opportunities to grow.