JermaineV.github.io

JermaineV
1

This Portfolio is a compilation of all the Data Science and Data Analysis projects I have done for academic, self-learning and hobby purposes.

#jekyll #python #tsql #jupyter-notebook

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Hello and welcome !

Hi! My name is Jermaine. Thank You for taking the time to view my GitHub Profile :smile:

About Me

🌱 I’m currently learning, AI, Neural Networks and MAchine Learning
👯 I’m looking to collaborate on Projects, blogs on DS, ML, AI.
💬 Please feel free to contact me with any opportunities: email

My Qualifications

Certificates and Academic transcripts

Microsoft T-SQL Certification

My Projects

Final college Data Science project:

This project/Report covers: Statistical analysis, PowerBI reporting and app deployment, Python, DML. All Scenarios, code and data source infomation are included in the report.

Tools used: PowerBi, Pandas, statistical methods.

Personal projects:

AI Communication Coach 2024(in progress): This project aims to develop a platform that utilizes Artificial Intelligence (AI) to assist users in improving their communication skills for public speaking and interviews:

Current Functionality: Speech Recognition: Capture and analyze user speech, Text Analysis: Perform sentiment analysis, keyword extraction, and named entity recognition, LLM Integration: Use pre-trained LLMs to generate responses based on user input. Video showcasing the initial features

Future Development: Enhance response generation using the LLM with context awareness and conversation history, Integrate feedback mechanisms to improve the coach's responses over time, Explore additional features like voice synthesis for coach responses or sentiment visualization.

Tools used: Python: Programming Language, Jupyter Notebook: Development environment, SpeechRecognition: Speech Recognition, NLP Libraries: NLTK, spaCy, TextBlob, Transformers: Hugging Face Transformers for text generation, (Optional) OpenCV: Computer Vision for future features

Credit Fraud Detection: Prediction/Analysis: Model that predicts transactional credit fraud by utilizing machine learning techniques.

Tools used: pandas, numpy, nltk, sklearn, seaborn, matplotlib

Stock Market Analysis for Tech Stocks: Analysis of technology stocks including change in price over time, daily returns, and stock behaviour prediction.

Tools used: Pandas, Folium, Seaborn and Matplotlib

Loan Dataset - Exploratory Data Analysis(EDA): Exploratory Analysis of the Prosper Loans company loan data using Pandas and Seaborn visualisations. Tools used: Pandas, Seaborn and Matplotlib

Titanic Dataset - Exploratory Analysis: Exploratory Analysis of the passengers onboard RMS Titanic using Pandas and Seaborn visualisations.

Tools used: Pandas, Folium, Seaborn and Matplotlib

Unsupervised Learning: Creating Customer Segments: Analyzing a dataset containing data on various customers' annual spending amounts (reported in monetary units) of diverse product categories for discovering internal structure, patterns and knowledge.

Tools used: scikit-learn, Pandas, Seaborn, Matplotlib, Pygame

Simple COVID-19 Self screening program using python: The programme will tell if someone has COVID-19 or not, based on a number of preset questions

Mini Project- CODING IN PROGRESS

Renewable Energy Usage Prediction: Work in progress: Using machine learning models to predict trends in renewable energy usage based on historical data and various socio-economic factors.