Integer Optimization in Python: A Practical Exploration through case studies and Beyond
Pooja (~pooja9) |
Description:
In this presentation, we will delve into the world of Integer Optimization in Python, uncovering its vast applications and remarkable potential. Through real-world examples, we showcase the power of mathematical optimization techniques, with intriguing use cases such as rider-driver matching and dynamic pricing control in ride-hailing platforms. Additionally, we explore how these techniques can play a pivotal role in Supply Chain optimization.
By harnessing the synergy of mathematical optimization and Python, we unlock the key to smarter decision-making and enhanced efficiency in intricate scenarios.
Prerequisites:
- Basic Python knowledge
- Basic Mathematics - Optimization, Linear Algebra
Speaker Info:
Pooja, a Lead Data Scientist at IQM, boasts a remarkable 8-year track record in automation, optimization, AI, and machine learning. She hold a post-graduate degree in Data Science and Automation from Indian Institute of Science. Her expertise has left a profound impact across various industries, notably in the Supply Chain domain within the E&P sector at Schlumberger and the dynamic world of Digital Advertising at IQM. With a strong grasp of data science methodologies and advanced analytics techniques, she tackles intricate challenges with precision. Pooja is regarded for her talent in developing modular, reusable, and robust data pipelines that incorporate fail-safe mechanisms and automatic recovery features. Recent pipelines developed by her have demonstrated scalability, handling requests ranging from 100k to 2M QPS with ease.