My name is Julián Mendoza, colombian, studied medicine from 2012 to 2019, then worked as a doctor for a year and a half but soon enough after graduating, I began to study a lot of math, mainly linear algebra and calculus, that because I wanted to become an AI engineer but I knew that road was gonna take a long time and a lot of time and preparation, it involved the process of first re learn math, then learn several programming languages, then become a data scientist and finally a machine learning enginer, so far the process involved first becoming a data analyst in 2020, then working as a data engineer during half of 2021 and all of 2022 until present, right now becoming a Data scientist. Maybe a couple of years from now, I’ll be able to lead machine learning complex projects in with medicine use, in fact I now implement machine learning algorithms everyday, one of my most persistent dreams has been to work in diagnostic and prognostic AI but that’s probably gonna have to wait right know, in the mean time I’ll just keep learning about more complex machine learning algorithms with DeepLearning.ai, Stanford and other sources, “Algoritmus” is the nickname I use in Linux and videogames, for me is a way of honoring Al-Juarismi father of algebra and algorithimics, it’s also his name translation to latin.
I’m currently studying machine learing algorithms in a much deeper way than before, including learning the code behind libraries like scikit-learn and tensor flow in order to have a much greater way to understand how to implement and perfectionate learning algorithms, not just call some functions that I have no idea how actually work, for me that’s a huge investment facing the future
I’ve always had a huge interest in science, mainly in neuroscience and everything that has to do with information processing in matter, that being said: information theory by Claude Shannon and Max tegmarks information realism are important prismas for me, but rather than a physicist (which I studied one semester before medicine), I like to be in places where all this advances are applied, maybe thats the reason behind medicine and engineering careers in my life. Here 2 papers in neuroscience where I participated as co-autor:
I’ven working on data mining, data science and data engineering for the past years, it’s been a ride and a great adventure for me since it allowed me to better understand the importance of data quality, data transform and proper data storage(warehousing) in order to prepare for machine learning projects. Most of the time I worked on ETL with DAGs in Apache Airflow, extraction and transform with Numpy, Pandas, PySpark, AWS, Azure and EDA univariate analysis but I also had time to implement basic linear and logistic regression algorithms for finance data. Maybe my favorite thing to do as a data engineer has been to process (transform) datasets using pandas, you can learn a lot from a dataset just by manipulating vectorized datasets, that’s what pandas is mostly about for me and it’s probably my favorite python library.