Dzimado Gabriel / Data Science and Analytics

Data Science Intern | Data Analytics | Machine Learning | Building real-world projects | Open to opportunities

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

Hi, I’m Dzimado Gabriel, an aspiring data scientist from Ghana. 🇬🇭

🔹 Learning SQL & Data Analytics
🔹 Building real-world projects
🔹 Passionate about solving problems with data
📌 Open to opportunities and collaborations

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

#AnalystlabAfric

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

Just completed my Week 5 Data Science project with @analystlabafric Experience Lab! 📊

I built machine learning models to predict patient appointment attendance using healthcare appointment data.

Models tested:
• Logistic Regression
• Decision Tree
• Random Forest

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

The Decision Tree performed best with ~61% accuracy and 62% No-Show recall.
Key lesson: Good ML starts with good data preparation, feature engineering, and the right evaluation metrics not just model accuracy.
#DataScience #MachineLearning #HealthcareAnalytics #Python #AI

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

@genesistvgh Hallalujah

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

• Designed the initial ML workflow

Data → Preprocessing → EDA → Features → Modelling → Evaluation → Prediction

Next: preprocessing, EDA, feature engineering & baseline modelling.

🔗 GitHub: https://t.co/URztjmnNha

#AnalystLabAfrica #DataScience #MachineLearning #Python

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

Week 4 | AnalystLab Africa Experience Lab
I’m working on a HealthConnect project focused on predicting patient appointment no-shows using machine learning.
This week, I:
• Defined no_show as the target
• Identified potential features
• Assessed key modelling considerations

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

Spartan mindset. 🛡️One piece at a time. Victory. 🏆
#DataScience #DataAnalytics #AnalystLabAfrica #Python #MachineLearning #LearningJourney

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

Week 3 done! @analystlabafric

I nearly gave up on this project because the workload was heavy balancing my Junior Data Scientist role at AnalystLab Africa, learning, and school.

https://t.co/J4BYZglee0

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

My solution? Break the big task into smaller pieces and face them one by one.

Data Science is not for the weak.

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

@genesistvgh #EVERYDAYWITHGOODISEVERYDAYINVICTORY

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

@inventorkhalifa Good bless you, man

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

@InsideKnust @DebwouyWalinky7 @spi_der_verse @kekeliwoelinam @Voice_of_Legon @CoHSSknust_ @abe_naaaa1 @niiannang517 Good job

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

@lattieeee Never little, Latifah, all the best

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

The dataset contains 918 patient records and 12 variables, with no missing values or duplicate records.

More to come as I move into the next stage.

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

I’ve worked on:
🔹 Business Understanding
🔹 Data Understanding & Quality Assessment
🔹 Data Preprocessing
🔹 Categorical Encoding Analysis
🔹 Scaling & Normalization Assessment
🔹 Correlation & Outlier Analysis
🔹 Feature Selection using Statistical Significance (p-values)

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

Key takeaway: Great data science starts with understanding the business problem before building machine learning models.

Tools: Python, Pandas, Matplotlib & Seaborn 🔗 GitHub: https://t.co/kxroUSL797
#AnalystLabAfrica #DataScience #EDA #Python #HRAnalytics #MachineLearning

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

Completed Week 1 of my Data Science Internship with @analystlabafric

This week, I explored the IBM HR Analytics dataset to understand employee attrition through business research, data inspection, and exploratory data analysis (EDA).

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

🔗 Live Demo: https://t.co/veiafVsnIv 💻 GitHub: https://t.co/Wyu1q8eAfJ
#MachineLearning #Python #DataScience #Streamlit #ScikitLearn #100DaysOfCode

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

I built and deployed my first end-to-end machine learning application

Student Performance Predictor uses multiple linear regression to estimate student performance based on study-related features.

[Dzimado Gabriel / Data Science and Analytics @GabrielDzimado]

What I learned:
• Data preprocessing & feature selection
• Model training and evaluation
• Model persistence with Pickle
• Building ML apps with Streamlit
• Deploying to the cloud
This project reinforced that deploying a model is just as important as building one.