Machine Learning Engineer passionate about using statistics and data to solve complex issues and draw insights.
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Programming Languages: Python, R, SQL, Java, JavaScript, HTML, CSS
Big Data and Analytics Tools: MySQL, Spark, Hadoop, MongoDB, Kafka, AWS database services, Tableau
Machine Learning: scikit-learn, TensorFlow, PyTorch, matplotlib, scipy, Supervised and Unsupervised Learning Algorithms, A/B testing, Hypothesis testing, Time series, Statistics
Google Cloud Certified Digital Leader
Achieved: December 2024
AWS Certified Cloud Practitioner
Achieved: August 2023
I used a convolutional neural network built with TensorFlow to create an image classification model to classify waste. I then connected model to raspberry pi to make a physical interface for users to interact with.
Video of Robot Github code
I performed an analysis of my chess.com data containing over 4000 games played! I created all visuals use Plotly in Python as well as Tableau.
View ArticleI built and deployed a website where users can upload a csv file and receive a preliminary analysis. I utilized the Pandas library in Python perform the analysis, and the Flask library to handle user input and integrate with the site.
Link to site Github code
I performed exploratory data analysis on two datasets containing information on Airbnb listings and their reviews. I cleaned and wrangled the data using Python with Numpy and Pandas. I visualized relationships between chosen variables using visualization libraries such as matplotlib, plotly, and seaborn.
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