AboutMe--D.Legorreta

About me

Hey this is Daniel Legorreta A highly skilled analytical consultant with a background in physics and mathematics (specialization: pure mathematics) and 12+ years of experience in developing and implementing statistical, machine learning, and deep learning models, as well as Big Data technologies. Dedicated, enthusiastic, and passionate about leveraging data to solve complex problems.

In my current role within a small agritech, I apply my skills as a Data Engineer, Machine Learning Engineer, and Data Scientist. This hands-on experience is complemented by my previous work as a consultant, researcher, and collaborator for numerous companies in various industries.

I usually work on topics such as:

Implementation of supervised and unsupervised models( standar ML or Deep Learning Models).

Creation of models and components for anomaly detection.

Development of code for processing in distribution systems.

Application of NLP techniques or LLMs models (chatbots, semantic search, classification of texts, etc.).

Creation of dashboard or visualizations.

A lifelong learner, I am enthusiastic about researching and implementing cutting-edge techniques and algorithms in personal projects. I prioritize staying up-to-date with the latest technological advancements and possess a deep appreciation for mathematics. My mathematical interests include algebraic topology, geometry, probability, and large graph theory, fields that I recognize as increasingly integral to Machine Learning, Deep Learning, and Computer Science.

Below you can find some research links on the relationship between mathematics and computer science.

Algebraic Topology and Data.

Geometry and Deep Learning.

Everything in Machine Learning is Probability, so I always recommend reading Kevin Murphy's book.

The graphics and the large graphics is a huge topic, so it is impossible to give just one reference.

Background and Experience

My major was in pure mathematics, I graduated from IPN in Mexico. I obtained solid foundations in mathematics and physics, which helped me to develop professionally in applications of mathematics to various problems in the industry.

My thesis work was on the application of algebraic topology in economics (paradox of social choice) under the supervision of the Phd. Jesus Gonzales Espino.

In parallel, I worked as a research assistant in Time Series and Complex Systems applications at the UPIITA-IPN Complex Systems Laboratory, under the supervision of Phd. Lev Guzman. I also worked as a research assistant in Mathematical Analysis under the supervision of Phd.Ramírez de Arellano.

I learned to program in C, C ++, Pytho, R, SQL and Bash before finishing college, and since 2008 I started to implement and develop components and models for various business cases. Since 2012 I specialized in Forecasting Models, I developed models for various companies, including Softtek, which predicted the demand for applications or systems (of more than 100 apps and systems).

After 2015 I specialized in Machine Learning and started using Deep Learning for different problems. In general, most of my projects have been on 3 topics:

Detection of Anomalies (Fraud, risks, anomalies)

Segmentation (Customer classification, post or text categorization, etc.)

Forecasting Models (time series, multi time series, regressive models, etc.)

Recently I have worked on projects that require the implementation of NLP techniques, both to process texts and to create chatbots or Agents.

If you want to review more about projects in my professional career, you can read my resume or you can send me a message and I will gladly answer you.