Implement Facebook Ad Campaign Analysis and Sales Prediction

[PRIYANSHU TIWARI]

Issue Title: Implement Facebook Ad Campaign Analysis and Sales Prediction

Description:

Implement a project to analyze Facebook Ad Campaigns and predict sales based on the available dataset. The project will involve data cleaning, exploratory data analysis (EDA), feature engineering, model training, and evaluation.

Tasks:

1. Data Cleaning:

   • Handle missing values.
   • Convert data types as needed.

2. Exploratory Data Analysis (EDA):

   • Generate summary statistics.
   • Create visualizations to understand data distribution and relationships.

3. Feature Engineering:

   • Create new features based on existing data.
   • Encode categorical variables.

4. Model Training:

   • Split data into training and testing sets.
   • Train multiple machine learning models (e.g., Linear Regression, Random Forest).

5. Model Evaluation:

   • Evaluate models using appropriate metrics (e.g., RMSE, MAE).
   • Select the best-performing model.

6. Documentation:

   • Document the analysis process.
   • Provide insights and recommendations based on findings.

Labels:

• enhancement
• data-science
• machine-learning