Fernando Flores
Data science, software development and engineering
I’m a Data scientist at the Coordination for Digital Education (AR) and Consultant in data science/engineering and R/Python software development. Previously, I was the Technical director of Tucma Software.
During my career I’ve worked in the public and private sector, within on-site and globally distributed teams in industries like software, IT, retail, education, energy and fintech, providing solutions for clients and users in America, Europe and Africa.
I helped companies across all stages of the data science life cycle, from kickstarting their data initiatives to statistical analytics, automation and application/dashboard development.
Do you need collaboration to achieve a measurable, data-driven improvement in your business? Feel free to book a consultation or connect with me on LinkedIn.
Interests
- Data Science
- Machine Learning
- Artificial Intelligence
- Math
- Big Data
- Data Ethics
- AI Safety
- Open Science
- Outreach
- Software Development
- Software Engineering
- Agile
Projects
(more projects to come…)
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wtkapi R package
R package to get atmospheric data from the NREL’s WIND Toolkit API.
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Toggl Dashboard
Extended Toggl dashboard in R with shinydashboard.
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Instagram R scraper
Instagram scraper in R using a third-party Java lib.
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Coursera | R Programming | Project assignment 1
Data Science specialization from Johns Hopkins University
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Coursera | R Programming | Project assignment 2
Data Science specialization from Johns Hopkins University
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Coursera | R Programming | Project assignment 3
Data Science specialization from Johns Hopkins University
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Coursera | Getting and Cleaning Data | Project assignment
Data Science specialization from Johns Hopkins University
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Coursera | Exploratory Data Analysis | Project assignment 1
Data Science specialization from Johns Hopkins University
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Coursera | Exploratory Data Analysis | Project assignment 2
Data Science specialization from Johns Hopkins University
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Coursera | Reproducible Research | Project assignment 1
Data Science specialization from Johns Hopkins University
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Coursera | Reproducible Research | Project assignment 2
Data Science specialization from Johns Hopkins University
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Coursera | Statistical Inference | Project assignments 1 and 2
Data Science specialization from Johns Hopkins University
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Coursera | Regression Models | Project assignment
Data Science specialization from Johns Hopkins University
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edX | 15.071x: The Analytics Edge | Coursework and Kaggle competition
The Analytics Edge course with R from MIT.
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edX | CS105x: Introduction to Apache Spark | Lab notebooks
Data Science and Engineering with Spark XSeries from University of California, Berkeley.
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edX | CS120x: Distributed Machine Learning with Apache Spark | Lab notebooks
Data Science and Engineering with Spark XSeries from University of California, Berkeley.
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edX | CS110x: Big Data Analysis with Apache Spark | Lab notebooks
Data Science and Engineering with Spark XSeries from University of California, Berkeley.
Talks
Debate | Let's talk AI
Discussion of the state-of-the-art AI research, and the safety and ethical considerations for building and working with machine learning systems.
Buró Coworking Meetup
How to provide remote software services
The Tucma Software experience of providing remote software development and tech services from Argentina to Europe, and how to innovate by facing the challenges in a culturally diverse environment.
TucumanValley Meetup
Debate | Battle of the frameworks
Software development frameworks aren't silver bullets. Discussion of the available solutions and the pros/cons for each type of project.
TucumanValley Meetup
My 2018 reading list
Yet another year of books! Ok, in comparison with the previous list, this one is much shorter. 2018 was a great year, full of challenges, work activities and fun, so I didn’t commit too much time to reading.
Without further ado, the books I’ve read were:
Spreading the word: My talk on data science with R
Last week I had a great time at the FLISoL 2018 Tucumán. First organized in 2005, the Festival Latinoamericano de Instalación de Software Libre (Latin American Free Software Install Fest) is the biggest event for spreading free software in Latin America and Spain.
Books I've read on 2017
For 2017, as part of my yearly planning, I tried to make more time to read several books that I had selected from my list (tsundoku, anyone?). It felt like a good challenge, both in planning and execution, and now I can say it was a great initiative to move forward in both my personal and professional life.
From january to december, I had read the following books:
Ethics in data science
Working with data is not only about algorithms, feature selection, business domain and all of the other technical topics usually brought up in discussions about the field. The current availability of data and processing power enables us to invent new ways to approach problems in society. Now more than ever, we as tech workers need to think how to act ethically and not just by the law. Fortunately in the past years we saw new initiatives like Fairness, Accountability, and Transparency in Machine Learning, books like Weapons of Math Destruction and courses like Data Science Ethics.
AI safety
Safety in Machine Learning and Artificial Intelligence is a very active research area. For a quick introduction to the subject in bite-sized chunks I strongly recommend to follow the work of Robert Miles. After gaining popularity in Computerphile videos he has now his own YouTube channel. Computerphile compiled a playlist about AI and Rob is producing a very interesting video series about a paper on concrete problems in AI safety here.