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Always Learning
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Always Learning
16 followers · 14 following

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Achievement: Pull SharkAchievement: Arctic Code Vault Contributor

Achievements

Achievement: Pull SharkAchievement: Arctic Code Vault Contributor

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danieltsoukup/README.md

Hello there 👋

I'm a Lead Educator & Team Lead at BrainStation, coordinating the delivery and content development of the full-time data science program. Previously, I was working on problems in data privacy, fairness in ML and building new generative models that produce the safest and most accurate synthetic data from complex data sources, such as mobility data. I have experience in various machine learning and deep learning frameworks, NLP methodology and have plenty of coding under my belt in Python.

I did my PhD at the University of Toronto and my following research was centred around understanding large, seemingly random and chaotic abstract mathematical objects (focusing on large graphs). How do local and global properties of certain structures interact and affect each other? Can a large network be sparse and highly connected at the same time? I have been focusing on such questions in graph theory, logic and combinatorics. Click for math publications here.

Further points of contact:

  • LinkedIn - reach out here to chat 💬
  • Website - more about my previous work 🤔

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  1. CivicTechTO/tRacket-dashboard CivicTechTO/tRacket-dashboard Public

    Noise monitoring dashboard built for the tRacket initiative.

    Python 7 6

  2. autoencoders autoencoders Public

    Autoencoder explorations: convolutional variational AE, denoising AE, and ensembles of randomized AE's for anomaly detection.

    Jupyter Notebook 2

  3. reinforcement_learning reinforcement_learning Public

    Experiments with reinforcement learning algorithms.

    Jupyter Notebook

  4. melanoma_regression melanoma_regression Public

    Quick analysis of why logistic regression can work on raw image data.

    Jupyter Notebook 1

  5. adventofcode adventofcode Public

    Advent of Code programming challenges.

    Python

  6. Toy-example for image segmentation w... Toy-example for image segmentation with k-means
    1 
    from matplotlib import pyplot as plt
    2 
    from sklearn.cluster import KMeans
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    img_path = # fill in
    
              
    
              
    
                5
                
    img = plt.imread(img_path)
    
              
    
          
    
    
    
  
    

    7.