a dedicated data scientist with a keen interest in extracting meaningful insights
from complex datasets. This README serves as an introduction to my proficiency in
data exploration, statistical analysis, and machine learning applications.
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Programming Languages: Proficient in Python (NumPy, Pandas, Scikit-Learn) and R
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Data Visualization: Skilled in Matplotlib, Seaborn, and Plotly. And others,
such as D3.js and ggplot2 -
Machine Learning: Experienced in regression, classification, clustering, and
neural networks. -
Big Data Technologies: Knowledgeable in Hadoop and Spark.
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Databases: Proficient in SQL and MongoDB.
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Tools: Well-versed in Jupyter, Git, and Docker.
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Natural Language Processing (NLP): Exploring the intersection of data science
and language to derive insights from unstructured data. -
Deep Learning Models: Investigating the latest advancements and applications of
deep learning in various domains. -
Healthcare Analytics: Applying data science techniques to healthcare data for
improved decision-making and patient outcomes.
I am open to engaging in collaborations, discussions, and learning opportunities. Please
feel free to reach out if you have inquiries, ideas, or simply wish to discuss data science!