This project was dedicated to enhance the quality of drinking water in
Aotearoa. Focusing was dissolvtion of Lead in Drinking Water which is called as plumbosolvency and understanding the
correlation of pressence of Lead with other determinands in Drinking Water. The project seeks to establish a
centralized national database for drinking water quality. Using machine learning techniques, it aims to predict the amount of Lead contaminants with
respect to the different zones, sources and Treatment Plants from
where the samples is been tested thereby data consolidating and
employing the predictive model
Embark on a tableau journey decoding hospital data. Explore varied encounters and their underlying reasons, painting a vivid healthcare landscape.
Analyze time spent in the Emergency Unit, revealing crucial insights into medical response and patient needs.
Dive into the duration of hospital residencies, uncovering diverse patient journeys and care dynamics.
Delve beneath surface encounters, unveiling the intricate interplay of health, wellbeing, and human experience.
This project focuses on leveraging data science techniques to analyze Amazon Kindle reviews data. Through machine learning, it conducts sentiment analysis to categorize feedback into positive, neutral, or negative sentiments. Additionally, the project preprocesses review text data by cleaning, lemmatizing, and removing stopwords, enabling deeper insights into customer behavior and product trends. The analysis includes examining the most frequently reviewed products and creating word cloud visualizations to highlight frequently occurring words in reviews.
This project aims to explore YouTube API functionality and analyze video data to debunk common assumptions about video performance on the platform, including the influence of metrics like likes and comments, video duration, title length, and tag usage.Investigating the significance of metrics like likes and comments in influencing a video's view count.
Assessing the impact of video duration on views and user interaction.
Exploring the correlation between title length and video views.
Examining the relationship between the number of tags used and the performance of videos.