Скачать или смотреть Predictive Modelling for Business Forecasting |Saurabh Chandurkar | Understanding Which Models best

I am thrilled to announced that I have successfully completed Task 2 at InternCareer.

Task 2: Predictive Modelling for Business Forecasting

Key Learning:

🔍 Identifying and Handling Missing Data: Learning how to detect, remove, or impute missing values to ensure dataset completeness.

🔍 Feature Selection: Identifying the most relevant features or variables that influence business outcomes is key to building effective models.

🔍 Model Selection: Understanding which models best fit different types of business problems is essential.
1) Linear Regression
2) Decision Trees
🔍 Model Evaluation: Assessing model performance using various evaluation metrics to ensure accuracy and reliability. Key metrics include:
1)RMSE
2)MAE
🔍 Interpreting Model Results: Understanding the outputs of predictive models and identifying the key drivers behind business predictions is crucial.

🔍 Forecasting Future Outcomes: Using trained models to predict future business outcomes, enabling proactive decision-making.

I'm incredibly grateful to have the opportunity to work as a Business Analytics Intern at InternCareer.

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