Motivations

As a proud alumnus of the National Agrarian University La Molina with a degree in Economics, I am deeply passionate about elucidating complex concepts that have captivated me—Game Theory, Econometrics, Corporate Finance, and Financial Risk. My journey has been about enriching these areas with a twist of programming, diving into the intricacies of Machine Learning and Deep Learning. I’ve crafted my portfolio with the hope that it serves as a valuable resource for you. Moreover, I aspire to not only assist you but also to empower you to create a web presence as dynamic as this one.

A mantra that has been instrumental in my growth and the genesis of this site is, “The quality of our lives is determined by the quality of the decisions we make.” This belief has been the compass that has guided me in my life and has greatly motivated my professional growth

In the spirit of sharing knowledge that inspires, here's a video that resonates with my vision and ethos: Discover a New Perspective.

Welcome to my world, where data meets decisions, and insights become actions.

Books That Shaped My Journey

• Finance
  by Zvi Bodie and Robert C. Merton
  A foundational book that offers a structured approach to understanding the complex world of finance and its various applications.
• Quantitative Investment Analysis
  by CFA Institute
  A practical guide on quantitative analysis techniques in investment management, essential for CFA candidates and professionals.
• Statistical Inference
  by George Casella and Roger L. Berger
  An advanced exploration of statistical theory, providing a deep dive into hypothesis testing and decision theory.
• Introduction to Linear and Matrix Algebra
  by Nathaniel Johnston
  Provides a concise introduction to the fundamental concepts of linear and matrix algebra used across science and engineering.
• Mathematics for Machine Learning
  by Marc Peter Deisenroth, A Aldo Faisal, and Cheng Soon Ong
  This book bridges the gap between mathematics and the application of machine learning techniques.
• An Introduction to Statistical Learning
  by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani
  A comprehensive introduction to the field of statistical learning, an essential toolkit for data analysis.
• Linear and Nonlinear Programming-Springer
  by David G. Luenberger and Yinyu Ye
  An advanced text that covers both the theory and applications of linear and nonlinear programming.