About me

My name is Daniel Legorreta, my major is physics and mathematics and my specialization is in pure mathematics, but for more than 8 years I have worked as an analytical consultant creating statistical models, machine learning and deep learning models and developing Big Data technologies. I am a dedicated professional, enthusiastic and passionate about my work.

I have often worked as an independent or independent consultant on some projects, but also for a long time I have worked in international financial institutions and international consulting in different projects.

I usually work on topics such as:

  • Implementation of supervised and unsupervised models.
  • Creation of models and components for anomaly detection.
  • Development of code for processing in distribution systems.
  • Application of NLP techniques (chatbots, semantic search, classification of texts, etc.).
  • Creation of dashboard or visualizations.

  • I have always loved learning and researching new techniques or algorithms and testing them in a personal project. I always try to update myself about the technologies. I love math, so I'm always reading, reviewing or learning something new about them. Especially in algebraic topology, geometry, probability and large graphics. Today, those subfields in mathematics are related to many topics in Machine Learning, Deep Learning and Computer Science in general.

    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 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.

    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.

    Courses and Certifications

    I only mention the most relevant courses for my professional career, with respect to the courses taken at the university I took courses up to masters in Mathematics, but I did not get my master's degree.

    AWS Certified Machine Learning

    Certification of Machine Learning Specialist by AWS

    Machine Learning

    Coursera Couse offered by Stanford

    Nanodegree Artificial Intelligence

    Part 1 of the Nanodegree in Udacity

    Machine Learning Terminology and Process

    Training and certification by AWS

    Machine Learning for Business Challenges

    Training and certification by AWS

    Process Model: CRISP-DM on the AWS Stack

    Training and certification by AWS

    Specialization

    Avanced Machine Leaning with Tensorflow on GCP

    Specialization

    Functional Programming in Scala