A goal-driven and result oriented Data Scientist who has been learning various data science techniques and skills such as predictive, descriptive and prescriptive data analysis, data visualization and storytelling, interpreting finding to drive optimization, statistics and probability, machine and deep learning in order to mine hidden gems located within large sets of structured and unstructured data with the aim of proffering edge cutting solutions and strategies. @OmololaDeborah
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This is a deep learning project (Computer vision) where I built real time face mask detection system. I built it using tranfer learning technique with MobileNetV2 as base model.
In this project (Natural Language Processing), I created a mental health chatbot named MentBot using deep learning (tensorflow.keras) and deployed using flask. The model is trained on chatbot.py file, the functions for generating chats are on processor.py while the codes for running the flask app is on app.py.
This a Natural Language Processing project where a collaborative filtering recommendation system was built using TF-IDF vectorization and Cosine Similarity.
This is a data analysis with SQL project. SQL was used to explore the data and to answer some analytical questions.
This an app hosted by Github and deployed by Streamlit of the above recommendation system model was built using TF-IDF vectorization and Cosine Similarity.
This is a web scrapping project aimed at scrapping the websites for the names and year of establishment of higher institutions in Nigeria using Python's Beautiful Soup.
With my data manipulation and visualization skills, I analyzed this test score results to know if test preparation courses are helpful. I explored the effect of parental education level on test scores.
Here, I built an article recommender system for both collaborative filtering and content based recommendation types. I used NLTK for pre-processing the data, k nearest neighbor (KNN) for content based recommendation and k means clustering for collaborative filtering.
This is the legendary Titanic ML competition. Its my first submission into ML competitions. Its a classification project on the prediction survival on the Titanic.
In this project, I analyzed the rating of different chocolate bars so as to look into the factors that make chocolate bars outstanding. My first Datacamp competition.