This is a Random Forest Regressor fine-tuned to predict the top tech jobs of 2025. Evaluation metrics such as MSE and MAE were used.
This table highlights the predicted top jobs for 2025 based on machine learning analysis.
| Actual Count | Position | Predicted Count |
|---|---|---|
| 8112 | Senior PHP Developer | 340.046579 |
| 6603 | Fullstack Web Developer | 249.704357 |
| 1595 | Software Engineer II - Fullstack | 231.141079 |
| 335 | Senior Lead Fullstack Developer | 136.610393 |
| 6990 | Security Software Engineer | 124.928202 |
| 738 | Senior SAP SD Inhouse Consultant | 118.556452 |
| 9595 | Software Developer in Test - Testing Framework | 104.560679 |
| 7938 | Frontend Entwickler - Typescript React Developer | 100.203060 |
| 5414 | Senior Frontend Developer React Typescript JavaScript | 74.510631 |
| 409 | Senior Fullstack Engineer | 65.983512 |
The model's evaluation metrics:
MSE: 1.420303488899371 MAE: 0.046526468271640996
This analysis utilizes a predictive model to forecast the demand for various positions in 2025. The Actual Count column references positions identified in the dataset, while the Predicted Count column showcases the model's predictions for their demand.
- Data preprocessing, including handling categorical variables and feature encoding.
- Prediction using a trained Random Forest regression model.
- Analysis of feature importance and evaluation using metrics such as Mean Squared Error (MSE).
- Clone this repository and run the provided script to reproduce the predictions or update the dataset.
- Visualize or update the table based on your organization's latest insights.