You will get I will create accurate sales forecasts to optimize planning using Python
Project details
Are you looking to predict future sales accurately?
I will develop a sales forecasting model tailored to your data.
This service includes:
✔️ Time series analysis
✔️ Feature engineering
✔️ Regression models
✔️ Forecast evaluation (MAE, RMSE)
✔️ Visualizations
Ideal for:
Retail businesses
E-commerce stores
Inventory planning
You will receive a clean and structured forecasting pipeline.
Share your data and I’ll send a preliminary analysis.
I will develop a sales forecasting model tailored to your data.
This service includes:
✔️ Time series analysis
✔️ Feature engineering
✔️ Regression models
✔️ Forecast evaluation (MAE, RMSE)
✔️ Visualizations
Ideal for:
Retail businesses
E-commerce stores
Inventory planning
You will receive a clean and structured forecasting pipeline.
Share your data and I’ll send a preliminary analysis.
Machine Learning Tools
ChatGPT, NumPy, pandas, Python, Python Scikit-Learn, scikit-learn, SQL, XGBoostWhat's included
| Service Tiers |
Starter
$60
|
Standard
$130
|
Advanced
$250
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 3 | Unlimited |
Number of Model Variations | 1 | 3 | 5 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
About Christian Junior
Machine Learning Engineer|Predictive Modeling & Data Analysis (Python)
Yaounde, Cameroon - 8:05 pm local time
Are you looking to turn your data into accurate predictions and actionable insights?
I am a Machine Learning Engineer specialized in predictive modeling and data-driven solutions. I help businesses:
✔️ Build classification and regression models
✔️ Predict customer churn and sales
✔️ Segment customers using clustering
✔️ Improve model accuracy and performance
✔️ Clean, analyze, and structure datasets
Recent Projects
- Telco Churn Prediction (Classification models, feature engineering, evaluation)
- Sales Forecasting using ML techniques
- Customer Segmentation with K-Means
- Deep learning experiments (CNN, RNN, NLP models)
Technical Stack
- Python (Pandas, NumPy, Scikit-learn, PyTorch)
- SQL (MySQL, PostgreSQL)
- Data visualization (Matplotlib, Seaborn, Power BI)
- Model evaluation & optimization
My Approach
- Clear understanding of business goals
- Structured data analysis
- Clean and reproducible code
- Clear interpretation of results
I focus on delivering practical, reliable, and well-documented solutions.
Let’s discuss your project.
Steps for completing your project
After purchasing the project, send requirements so Christian Junior can start the project.
Delivery time starts when Christian Junior receives requirements from you.
Christian Junior works on your project following the steps below.
Revisions may occur after the delivery date.
Data preparation
Collect and clean data (quantities, revenues, dates, promotions, events). Identify influential variables (seasonality, marketing campaigns, holidays, etc). Transform the data to make it usable (encoding, normalization, creation of temporal features).
Model design and training
Choose the appropriate algorithms depending on complexity(ARIMA, Random Forest, Gradient Boosting) Divide the data into train and test sets Train the model and adjust the hyperparameters Evaluate performance using prediction metrics (MAE, RMSE, MAPE)