Am passionate about the use of data to derive models to drive product-driven applications. Some of the major tools in my arsenal are SQL, Python, Scikit-Learn, Tensorflow, Huggingface, Excel, PowerBI and Google Looker. I have a proven history of using data to build data-driven products especially in the Fin-tech industry. I have worked on using data to improve the feature of applications using sentiment analysis of customer surveys (using PowerBI and Python). This data driven decision was implemented by the product and technology team to improve the user experience of the product. My skill-sets cuts across statistics, data analysis, data visualization and Critical Thinking. One of my major strengths is the ability to work and deliver as at when due. I am data driven and possess strong communication and interpersonal skills which means I can seamlessly fit into any team.

I pride myself on being a self-starter, problem solver, and excellent communicator with the ability to breakdown data to drive business driven decisions to stakeholder

I occasionally use different technologies & platforms, however my current favorites are:

✨  My Portfolio

I am passionate about the use of data, to come up with models to make data-driven decisions.

My Portfolio

• Predictive Analytics and Machine Learning:

  • Automobile Resale Value Forecaster
    The "Automobile Resale Value Forecaster" is a machine learning project focused on predicting the resale value of automobiles using a regression model and a simple neural network. This project utilizes a simple neural network built with TensorFlow, providing insights into the resale value based on various vehicle attributes. Here I used the HorsePower of these Used Care to determine its resale value.
    

• Amazon Q Sentiment Analysis:

  • Amazon Q Sentiment Analysis
    This mini-project came as a result of my curiosity with the whole hype of AI which seems to be dominating the technology landscape. Amazon Comprehend and Amazon Sagemaker Studio played a crucial role in carrying out the Sentiment Analysis of Amazon Q. With Amazon Comprehend’s advanced NLP capabilities such as entity recognition, key phrase extraction, and sentiment analysis, I am able to uncover valuable insights from the tweets extracted from Twitter.
    

🛠️  Languages and Tools

👩🏽‍💻 All of my projects are available at Github

🔗  Let us be friends