Visualize Solutions

Karachi Division, Sindh, Pakistan

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Summary

🤩

Rockstar

Visualize Solutions is a software engineer and data scientist specializing in mathematical and machine-learning visualizations, with four years of professional experience and a decade of regional exposure across Dubai and Pakistan through the VES initiative. They author the Iris Series—an extensive Python-driven visual math project of ~8,000 vector graphics—that teaches concepts from arithmetic to machine learning through interactive plots and notebooks. Their open-source work focuses on probability, statistics, linear algebra, color spaces, and classifier visualizations using NumPy, Matplotlib, Seaborn, and scikit-learn, emphasizing interpretability and pedagogy. Practical contributions include implementing Dirichlet visualizations, Mahalanobis distance analyses, and decision-boundary demonstrations on the iris dataset. Based in Karachi, they blend engineering rigor with educational design to make abstract math tangible for learners and businesses. Less obvious: their projects double as modular teaching materials that can be repurposed for internal data literacy and client-facing analytics demos.

3 years of coding experience

Github Skills (28)

algorithm10

data-visualizations10

visualization10

seaborn10

matrix10

python10

data-science10

matplotlib10

scikit10

mathematics10

pandas10

statistics10

machine-learning10

data-visualisation10

machine-learning-algorithms10

Programming languages (1)

Jupyter Notebook

Github contributions (5)

Visualize-ML/Book2_Beauty-of-Data-Visualization

Feb 2023 - Mar 2023

Book_2_《可视之美》 | 鸢尾花书：从加减乘除到机器学习，欢迎批评指正

Role in this project:

Data Scientist

Contributions:59 commits, 314 pushes, 3 branches in 18 days

Contributions summary:Visualize contributed to the visualization of data within a machine learning context, specifically focusing on the exploration and representation of the HSV and RGB color spaces using scatter plots and surface plots. Their work involved creating functions and visualizations related to color spaces and the display of Gaussian distributions. The commits highlight an engagement with data visualization techniques, including the generation of contour plots.

Visualize-ML/Book7_Visualizations-for-Machine-Learning

Oct 2022 - Jan 2023

Book_7_《机器学习》 | 鸢尾花书：从加减乘除到机器学习；欢迎批评指正

Role in this project:

Data Scientist

Contributions:36 commits, 110 pushes, 3 branches in 3 months

Contributions summary:Visualize contributed code primarily focused on data visualization and the application of machine learning algorithms. Their work involved implementing and demonstrating various classification models, including k-NN, Nearest Centroid, Linear Discriminant Analysis, and Gaussian Mixture Models, using the scikit-learn library. The user also created interactive visualizations using matplotlib, including decision boundary plots and silhouette analysis, showcasing a strong emphasis on data exploration and model interpretation. The code demonstrates proficiency in handling and visualizing datasets related to machine learning problems.

pythonlinear-algebradata-sciencemachine-learning-algorithmsmachine-learning

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