Gouthami Venkatesh the Analyst Portfolio

Data Analyst | Crafting Data-Driven Stories with SQL, Python, and Machine Learning | Delivering Insights that Drive Impact @GouthamiTheAnalyst

COVID-19 Chest X-ray Image Classification Using Deep Learning

Built a model using CNNs (AlexNet, ResNet18) to classify normal, COVID-19, and viral pneumonia cases from chest X-ray images. Utilized Python and PyTorch with advanced preprocessing techniques. Achieved over 95% accuracy, providing a potential diagnostic tool for healthcare professionals

Skills: Deep Learning ยท PyTorch ยท Healthcare Analytics ยท AI for Healthcare ยท Model Evaluation

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House Price predictions

This analysis predicts *median_house_value* using features like location, housing age, and income. Key findings show that *median_income* has the strongest correlation with house value.

Florida College Map

This interactive map visualizes: Colleges (Public vs. Private) based on their admission rates and undergraduate population. Major cities with a population greater than 50,000, highlighting proximity to these colleges. This project helped me enhance my skills in data merging, geographic visualizations, and interactive dashboards

Sales Forecasting using ARIMA model

"Developed a sales forecasting model using ARIMA to predict future sales trends based on historical data. Optimized the model to achieve accurate forecasting, aiding in strategic decision-making and inventory management."

Publication: Prediction of Autism Spectrum Disorder

This publication discusses the application of machine learning algorithms to predict Autism Spectrum Disorder based on various features. It highlights the methodology and results obtained, contributing to the understanding of this condition and potential diagnostic improvements.

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Publication: Prediction of Autism Spectrum Disorder

This publication discusses the application of machine learning algorithms to predict Autism Spectrum Disorder based on various features. It highlights the methodology and results obtained, contributing to the understanding of this condition and potential diagnostic improvements.