https://github.com/ali-jalil88/mlflow-dl-ann

Gender Classification Using ANN with MLflow
https://github.com/ali-jalil88/mlflow-dl-ann

adam dense labelencoder metrics mlflow optimizer standardscaler

Last synced: 19 days ago
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Gender Classification Using ANN with MLflow

• Host: GitHub
• URL: https://github.com/ali-jalil88/mlflow-dl-ann
• Owner: Ali-jalil88
• Created: 2024-11-21T11:02:07.000Z (about 1 month ago)
• Default Branch: main
• Last Pushed: 2024-11-21T11:28:32.000Z (about 1 month ago)
• Last Synced: 2024-11-21T12:18:21.138Z (about 1 month ago)
• Topics: adam, dense, labelencoder, metrics, mlflow, optimizer, standardscaler
• Language: Jupyter Notebook
• Homepage:
• Size: 356 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Gender Classification Using ANN with MLflow

![Gender Classification Workflow](https://raw.githubusercontent.com/Ali-jalil88/Mlflow-DL-ANN/refs/heads/main/pic.webp)

## 1. Overview of the Dataset

### Dataset Description:

The dataset contains biometric or behavioral data (e.g., height, weight, voice pitch) for predicting gender. The task is binary classification: **Gender**.

### Features:

- **Height (cm)**

- **Weight (kg)**

- **Voice_Pitch**

- Other relevant features...

### Target Variable:

- **Gender**

  - `0 = Male`

  - `1 = Female`

### Dataset Split:

- **Training Set**: 70%  

- **Validation Set**: 15%  

- **Test Set**: 15%

---

## 2. Objective

Develop and train an **Artificial Neural Network (ANN)** for classifying gender, utilizing **MLflow** to track and manage the experiment.

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## 3. Experiment Workflow

### Data Preprocessing

#### Handle Missing Values:

- Impute missing data with **mean** or **median** for numeric features.

#### Feature Scaling:

- Normalize numeric features using `StandardScaler`.

#### Data Splitting:

- Split the dataset into **training**, **validation**, and **test** sets.

## Links:

- **[Project Notebook](https://www.kaggle.com/code/alialarkawazi/gender-classification-dl-ann)**

- **[Dataset](https://www.kaggle.com/code/alialarkawazi/gender-classification-dl-ann?select=Transformed+Data+Set+-+Sheet1.csv)**