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Earning XP and Leveling Up
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Earning XP and Leveling Up

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ordovas/README.md

Data Scientist

Python | Machine Learning | Deep Learning | LangChain | Numpy | Pandas | Computer Vision | Natural Language Processing | Azure ML | Matplotlib | LaTeX | IRAF | MongoDB | MySQL | TensorFlow | Keras | API | Web Scraping

Hi there! I’m a versatile data science consultant based in Madrid. I’m capable of helping clients to solve their problems creatively and handle complex databases to obtain precise, understandable and useful insights. With a strong scientific background and extensive experience as a Data Scientist, I thrive in the dynamic environment of professional consulting. Having contributed to cross-functional client projects and internal initiatives focused on ML pipelines, I excel in teamwork, meeting deadlines, and effectively communicating complex ideas to non-technical audiences. As a curious and fast learner, I continuously embrace the latest data science techniques, ensuring adaptability and delivering tangible results. My research expertise in the astrophysics field allows me to mine those shiny data spots hidden in the darkness.

Certifications:

🌍 Terrenal work:

I’m always practicing and learning new tools to improve my data scientist and coding skills. These are some examples I did unrelated with my current job:

-Library to create a LLM agent to create and execute on-the-fly code to perform simple DS tasks

-Dice Scores Recognition in image/video

-Predicting the numeric ratings of Amazon books review based exclusively on the text of the review.

-A small Web scraping and RegEx exercise to mine the japanese hardware and softare video game sales.

Other examples of my work outside GitHub:

-Microsoft IoT blog post: Retail Self-checkout Object Detection Solution

-Presentation I gave (with a coworker) about LLMs performance with mathematical operations.

-Cognizant blog post about a Computer Vision solution we've worked on.

Feel free to have a look at other repositories with other exercises, learning notebooks & code or simple tests, even if they are uncomplete or not interesting enough to be shown in the profile.

🌌 Celestial work:

I've worked analyzing the relation (or lack of it) between the optical extinction, X-ray absorption and classification of Active Galactic Nuclei. Apart from that I've also worked using the k-means unsupervised classification algorithm applied to astronomical data.

You can find my astrophysics research papers and other contributions in ADS, or read my PhD Thesis PDF if you want (text in english, summary in both spanish and english).

Pinned Loading

  1. dice-scores-recognition dice-scores-recognition Public

    Dice Scores Recognition in images and live video using CNN.

    Jupyter Notebook 9 1

  2. vg_jp_sales vg_jp_sales Public

    A small Web scraping and RegEx exercise to mine the japanese hardware and softare video game sales.

    Jupyter Notebook

  3. pandas-project pandas-project Public

    A word frequency based analysis of sharks attacks

    Jupyter Notebook 1

  4. amazon_books_reviews amazon_books_reviews Public

    Predicting the numeric rating of Amazon books review based exclusively on the text of the review.

    Jupyter Notebook

  5. pipelines-project pipelines-project Public

    The 500 Greatest Albums of All Time: An exercise of analysis of the database with extra information gathered using the Spotify and Wikipedia APIs

    Jupyter Notebook

  6. kaggle-diamonds kaggle-diamonds Public

    Kaggle competition: Predicting diamonds prices

    Jupyter Notebook