Franklin Ike

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About Me

Hi, I’m Franklin Ike, a dedicated Data Scientist and Machine Learning Engineer passionate about turning raw data into intelligent insights and deployable models. I thrive in solving business problems using data-driven strategies and advanced machine learning techniques.

I’ve earned certifications from globally recognized programs, including:

Data Science - 3MTT Nigeria
Machine Learning Foundations - AWS Educate
Career Essentials in Generative AI - Microsoft & LinkedIn
Global AI Bootcamp 2025 - Global AI Community
Artificial Intelligence & Robotics - Nigeria Computer Society (NCS)

Projects I’ve built and contributed to include:

Sales Data Analysis: Involving data cleaning, visualization, and insight extraction
Covid-19 Data Analysis: Exploring trends, vaccination impact, and insights through visualization
Fraud Detection Model: Using Random Forest Classifier for predictive analytics
Diamond Price Prediction: Using Random Forest Regressor
Credit Risk Assessment: Using Random Forest Classifier
Fake News Detection: Using SVM (LinearSVC)
Employee Burn Rate Prediction: Using Gradient Boosting Regressor
Logistics Delivery Delay Prediction: Using Gradient Boosting Classifier
Customer Purchase Prediction: Using Neural Networks
Customer Churn Prediction: Using Decision Tree Classifier

My current focus includes:

Agentic AI workflow using LangChain and CrewAI
Exploring big data analytics tools, Hadoop and Snowflake

I’m a problem solver, continuously learning and experimenting with cutting-edge tools and techniques. Whether it’s developing predictive models, conducting in-depth exploratory data analysis, or communicating data insights to stakeholders, I bring both technical precision and a strong business mindset.

I’m currently open to collaboration, job, or freelance opportunities in data science, machine learning, and AI. Let’s create impactful, intelligent systems together.

My Skills

Python

100%

Pandas

100%

Numpy

100%

Matplotlib

100%

Seaborn

100%

Descriptive stats, hypothesis testing, distributions

100%

Linear algebra, calculus, matrix operations

95%

CrewAI

80%

Jupyter Notebooks / Google Colab

100%

SQL

100%

Git & GitHub

100%

APIs

100%

Scikit-learn

100%

Tensorflow

90%

NLTK

75%

Streamlit

100%

Projects

Sales Data Analysis

Performed end-to-end analysis on retail sales data involving data cleaning, transformation, and visualization to extract actionable business insights and highlight sales trends across products, regions, and time periods.

Live Demo GitHub

Covid-19 Data Analysis

Explored global and regional COVID-19 trends using real-time datasets, analyzing infection rates, vaccination progress, and mortality through statistical graphs and dashboards to inform public health decisions.

Live Demo GitHub

Financial Fraud Detection

Built a predictive classification model using the Random Forest algorithm to detect fraudulent transactions, improving fraud identification accuracy while reducing false positives.

Live Demo GitHub

Credit Risk Assessment

Created a credit scoring model using Random Forest Classifier to assess loan applicants’ risk levels and assist financial institutions in making informed lending decisions.

Live Demo GitHub

Diamond Price Prediction

Developed a regression model using Random Forest Regressor to accurately predict diamond prices based on features like carat, cut, color, clarity, and dimensions.

Live Demo GitHub

Customer Purchase Prediction

Trained a neural network model to predict customer purchase intent based on behavioral and transactional data, aiding in personalized marketing and conversion strategies.

Live Demo GitHub

Fake News Detection

Implemented a text classification system using SVM (LinearSVC) to distinguish between real and fake news articles based on natural language features and TF-IDF vectorization.

Live Demo GitHub

Employee Burn Rate Prediction

Applied Gradient Boosting Regressor to forecast employee burnout rates based on HR-related features, helping organizations anticipate attrition risks and improve workplace satisfaction.

Live Demo GitHub

Logistics Delivery Delay Prediction

Built a classification model using Gradient Boosting Classifier to predict delays in logistics delivery systems, enabling more accurate time estimations and operational planning.

Live Demo GitHub

Customer Churn Prediction

Built a decision tree model to predict customer churn for a telecom company using DecisionTreeClassifier. Customer churn refers to when a customer stops doing business with a company.

Live Demo GitHub

Contact Me

You can also reach me via:

Email GitHub LinkedIn