Home of AutoViz, AutoViML and featurewiz
Machine Learning Engineer
Summary
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RockstarHome of AutoViz, AutoViML and featurewiz is a machine learning engineer with seven years of experience building practical AutoML and visualization tools. They contribute core functionality to widely used open-source projects like AutoViz and Auto_TS, enabling single-line workflows for dataset visualization and time series modeling (ARIMA, SARIMAX, VAR, Prophet, XGBoost). Comfortable across model-building, interpretability and plotting, they focus on making complex ML accessible and reproducible for practitioners. Their GitHub contributions show hands-on creation and iterative refinement of main library modules, not just peripheral fixes. Based in the United States, they blend data-scientist instincts with engineering rigor to deliver production-ready tooling.
6 years of coding experience
Github Skills (13)
scikit-learn10
data-visualizations10
pandas10
machine-learning10
data-visualization10
data-visualisation10
visualization10
time-series10
visualizations10
automl10
python10
scikit10
arima9
Programming languages (3)
Github contributions (5)
AutoViML/AutoViz
Jul 2019 - Dec 2022
Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
Role in this project:
Data Scientist
Data ScientistContributions:1 review, 97 commits, 22 PRs in 3 years 6 months
Contributions summary:Home's commits primarily involve modifications to the `AutoViz_Class.py` file, suggesting a focus on the core functionality of the AutoViz tool. These changes include updates to charts and plotting, particularly for categorical variables and distribution plots. The commits indicate efforts to refine the visualizations produced by the tool and improve its ability to analyze and present data insights.
xgboostpythonvisualizeholoviewsdata-science
AutoViML/Auto_TS
Dec 2019 - Aug 2022
Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Created by Ram Seshadri. Collaborators welcome.
Role in this project:Data Scientist
Data ScientistContributions:7 reviews, 111 commits, 32 PRs in 2 years 8 months
Contributions summary:Home appears to be a data scientist focused on time series analysis and forecasting using the `auto_ts` library. The initial commit adds the core `Auto_TimeSeries_Final.py` file, indicating the creation of the library's main functionality. Subsequent commits involve making modifications and merging changes to improve the software. The commit messages suggest iterative development and refinement of the library.
xgboostforecastingpythontime-series-analysissklearn
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