Projects

  • Climate TempTrend Hub
  • India Unemployment Rate

Climate TempTrend Hub

The repository conducts an analysis of global average temperature anomaly data, using Python's pandas library for data manipulation and various forecasting models. It preprocesses the data, conducts time series analysis, and splits it for training and testing. Forecasting models like ARIMA, ETS, Prophet, GBR, and LSTM are implemented and compared based on performance metrics. The LSTM model shows superior performance, offering predictions for future temperature anomalies. Overall, the repository provides valuable insights into climate trends and variability.

India Unemployment Rate

The research aims to understand the impact of the COVID-19 pandemic on India's labor market by analyzing monthly unemployment data from January 2018 to February 2023. The project aims to identify shifts in unemployment rates, examine sector-specific impacts, assess demographic disparities, and forecast future unemployment trends. The evaluation will employ qualitative and statistical tests to assess data collection, preprocessing, analysis efficacy, and model prediction accuracy.

About Me

Hello, I'm Emuejevoke Eshemitan, a passionate data professional specializing in Machine Learning Engineering and Data Science. My portfolio showcases projects reflecting my dedication to leveraging data for insightful and innovative solutions.
As a Machine Learning Engineer, I excel in designing cutting-edge models using TensorFlow and scikit-learn, building scalable data pipelines, and deploying them in production environments.
As a Data Scientist, I analyze valuable patterns, develop predictive models, and communicate insights through impactful visualizations.
Let's collaborate on a data-driven journey! Explore my portfolio for more.

Phone

+234 902 436 2357

Location

Lagos, Nigeria