Description

Welcome to the world of predictive real estate! In this analysis, we'll employ the powerful tool of linear regression to delve into the captivating realm of house prices. By scrutinizing key variables, we'll unravel the intricate relationships influencing property values. To be able to read the secrets hidden in data and craft a reliable model to forecast house prices with precision and finesse click on Forecasting House Prices with Machine learning.and the Code used for implementing it is available Github.

I can help you for

• Exploratory analysis of a dataset.
• Creation of clean and reproducible reports using R Markdown.
• Application of statistical methods on your dataset.
• Creation of custom scripts for analysing your data automatically

Example:

• I'm the author of several scientific publications where I was in charge to explore and understand complex dataset in order to answer scientific questions.
• I recovered information about crypto currency prices on different exchanges and explored the data looking for arbitrage opportunities.

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I can help you with:

• Creation and review of graphs for scientific publication.
• Development of data application using R and Shiny.
• Creation of custom data visualization for the web using d3.js.
• Dashboard creation for real time data analysis.
• Visualization of geospatial data.

Example:

• A website describing research results on mental disorders comorbidity.
• Data to viz: a decision tree leading to the most appropriate chart type for your data.
• See many more examples in the portfolio section of this website.

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Description

Through an intensive research and analysis on Accident. i came up with a research paper called UK road Accident Insight Analysis . This research uncovers crucial insights into the occurrence of road accidents in the United Kingdom within the year 2005 to 2014 By analyzing accident rates, identifying patterns and hotspots, unraveling causal factors,assessing the impact on public health and safety, and providing recommendations for policy and safety initiatives, this study contributes to evidence-based decision-making and strives for enhanced accident prevention and improved public safety.

The data utilized in this analysis was obtained from the Kaggle website, a renowned platform for accessing and exploring diverse datasets. we can click on Kaggle uk Road accident .to download the data used for the research

The shiny application allows to visualize the geographic distribution of any trait. It allows to custom color scales, region shape and to apply a cartogram algorithm to the map. Moreover, the tool allows one to upload its own data to benefit this dataviz tool.

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Description

This study talks about an automated system with high precision for malaria diagnosis using CNN and MlP.

Malaria Detection Enhanced CNN and MLP Classifiers Developed. we can see the code use to implement the classifier by clicking on the Github code. from the Optimization result the CNN outperforms MLP classifier. The tool was created using google colab and The blog or Article can be asses by clicking on malaria Article . The source code of the blog are on KAGGLE WEBSITE.

Description

Sentimental Analysis It involves analyzing customer reviews, social media posts, and other relevant data sources to gain insights into the positive, negative, or neutral sentiments expressed by consumers. I conducted a study focusing on sentiment analysis specifically related to women clothing also you can access the code used for the project by clicking on code to see the machine learning models uses for the building of the Sentiment .

we can also download the dataset from the link below. TO see the source of where data is gotten fromJama Psychiatry. Several interactive graphs are available with export options and more. The tool was created using R and Shiny, plus several Html widgets for interactivity.

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Description

This Article explores the potential of AI lie detectors to revolutionize various sectors, particularly in crime investigation, and highlights ethical frameworks for responsible deployment, considering privacy, security, and ethics. By implementing citizen-centric programming, public participation, and reducing biases, governments can harness AI technology to enhance services while protecting citizens' rights and well-being. To access the full article and delve deeper into the subject matter, please click on the Title: Developing a framework for the ethics of AI-based lie detection in government .

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Description

This research utilized Machine Learning techniques to analyze car datasets from Kaggle, employing methods such as linear regression, classification, and clustering. The study aimed to predict car prices and classify car conditions. Click on Automobile prediction to read more. The Model accuracy was evaluated using various metrics, and the dataset underwent preprocessing to ensure data quality. The results showed successful implementation of predictive models and clustering, but hierarchical clustering faced limitations with larger datasets. Future work should explore more robust algorithms and delve into other factors influencing car prices .

Description

The GreenTech challenge is a Dataviz competition launched by the French Ministery of environment that took place in 2017. A huge dataset concerning pesticides in France has been released, and the goal was to build innovative visualizations to sensibilize and inform citizen concerning the french situation over the past 6 Years.

We decided to make a team of 4 friends and built a ShinyApp that allows to efficiently explore this dataset. The app is composed by several sheets, each targeting a specific theme. This tool should allow you to understand what happens in your neighbourhood and in the entire country. It is also studied to improve your genereal knowledge concerning pesticides.

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Description

UNICS is a web app that helps you computing the standard error of allele frequency estimations of future pool-sequencing experiments based on different parameters. You can use it trough the online version and read the related publication.

Application looks like this:

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Description

I created an R script that recovers all tweets containing the hashtags #surf Using Power BI's advanced analytics and visualization capabilities, the HR team successfully identified attrition trends and root causes, enabling data-driven decision-making to implement targeted retention strategies, ultimately reducing employee turnover and fostering a more engaged workforce .

Here is an overview of the result:

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