| 16 | Introduction to Natural Language Processing | [Natural Language Processing](NLP/README.md) | tbd | [lesson]() | Stephen |
| 16 | Introduction to Natural Language Processing | [Natural Language Processing](NLP/README.md) | tbd | [lesson]() | Stephen |
| 17 | Romantic Hotels of Europe ♥️ | [Natural Language Processing](NLP/README.md) | tbd | [lesson]() | Stephen |
| 17 | Romantic Hotels of Europe ♥️ | [Natural Language Processing](NLP/README.md) | tbd | [lesson]() | Stephen |
| 18 | Romantic Hotels of Europe ♥️ | [Natural Language Processing](NLP/README.md) | tbd | [lesson]() | Stephen |
| 18 | Romantic Hotels of Europe ♥️ | [Natural Language Processing](NLP/README.md) | tbd | [lesson]() | Stephen |
| 19 | Romantic Hotels of Europe ♥️ | [Natural Language Processing](NLP/README.md) | tbd | [lesson]() | Stephen |
| 19 | Romantic Hotels of Europe ♥️ | [Natural Language Processing](NLP/README.md) | tbd | [lesson]() | Stephen |
| 20 | Introduction to Time Series Forecasting | [Time Series](Time-Series/README.md) | Introduction to Time Series Forecasting | [lesson]() | Francesca |
| 20 | Introduction to Time Series Forecasting | [Time Series](Time-Series/README.md) | Introduction to Time Series Forecasting | [lesson](Time-Series/1-Introduction/README.md) | Francesca |
| 21 | ⚡️ World Power Usage ⚡️ Time Series Forecasting with ARIMA ⚡️ | [Time Series](Time-Series/README.md) | Time Series Forecasting with ARIMA | [lesson]() | Francesca |
| 21 | ⚡️ World Power Usage ⚡️ Time Series Forecasting with ARIMA ⚡️ | [Time Series](Time-Series/README.md) | Time Series Forecasting with ARIMA | [lesson](TimeSeries/2-ARIMA/README.md) | Francesca |
| 23 | Help Peter avoid the Wolf! 🐺 | [Reinforcement Learning](Reinforcement/README.md) | tbd | [lesson]() | Dmitry |
| 23 | Help Peter avoid the Wolf! 🐺 | [Reinforcement Learning](Reinforcement/README.md) | tbd | [lesson]() | Dmitry |
| 24 | Real-World ML Scenarios and Applications | ML in the Wild | Interesting and Revealing real-world applications of classical ML | [lesson](Real-World/1-Applications/README.md) | All |
| 24 | Real-World ML Scenarios and Applications | ML in the Wild | Interesting and Revealing real-world applications of classical ML | [lesson](Real-World/1-Applications/README.md) | All |
Now that you have built one web app using a trained Regression model, use one of the models from an earlier Regression lesson to redo this web app. You can keep the style or design it differently to reflect the pumpkin data. Be careful to change the inputs to reflect your model's training method.
| A new web app is presented | The web app runs as expected and is deployed to the cloud | The web app contains flaws or exhibits unexpected results | The web app does not function properly |