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updated broken links #7

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21 changes: 6 additions & 15 deletions 02.azure-ml/01.presentation.md
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Expand Up @@ -8,21 +8,12 @@ Since 1985 [Proge-Software](https://www.progesoftware.it/) produces high-technol
- Site: https://www.progesoftware.it/
- LinkedIn: https://www.linkedin.com/company/proge-software/



### Caterina Frollo

*Junior Data Scientist* per Proge-Software

- GitHub: https://github.com/poessevero
- LinkedIn: https://www.linkedin.com/in/caterina-frollo/

## Agenda

1. [Presentation](01.presentation.md) :clock9: **(09:00)**
1. [Presentation](01.presentation.md) :clock0: **(00:00)**
- Who Is Proge-Software
- Who Am I
2. [Introduction](02.introduction.md) **(09:15)**
2. [Introduction](02.introduction.md) **(00:15)**
- Python
- Pandas
- NumPy
Expand All @@ -38,7 +29,7 @@ Since 1985 [Proge-Software](https://www.progesoftware.it/) produces high-technol
- Forecast Analysis
- ARIMA: Autoregressive integrated moving average
- Prophet
3. [Azure Machine Learning Studio](03.azure-machine-learning-studio.md) :clock10: **(10:00)**
3. [Azure Machine Learning Studio](03.azure-machine-learning-studio.md) :clock1: **(01:00)**
- What is Azure ML Studio
- Differences with Classic version of the platform
- Why do we need it
Expand All @@ -52,16 +43,16 @@ Since 1985 [Proge-Software](https://www.progesoftware.it/) produces high-technol
- Work with Computes
- Web
- Command Line
4. [Demo](04.demo.md) :clock1030: **(10:30)**
4. [Demo](04.demo.md) :clock130: **(01:30)**
- Setup Azure ML Studio
- Data
- Preprocessing the Data
- Code explanation
- Train the Prophet model and prediction of the trend
- Test the Prophet model
5. [Where to go next](05.where-to-go-next.md) **(10:50)**
5. [Where to go next](05.where-to-go-next.md) **(01:50)**
- Neural Networks
- Tensorflow
- Keras
- PyTorch
6. [Q&A](06.q&a.md) **(10:55)**
6. [Q&A](06.q&a.md) **(01:55)**
16 changes: 8 additions & 8 deletions 02.azure-ml/02.introduction.md
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Expand Up @@ -290,18 +290,18 @@ It works best with time series that have strong seasonal effects and several sea
- [https://insights.daffodilsw.com/blog/9-machine-learning-examples-from-day-to-day-life](https://insights.daffodilsw.com/blog/9-machine-learning-examples-from-day-to-day-life)
- [https://towardsdatascience.com/](https://towardsdatascience.com/)
10. Preprocessing data
- [(https://en.wikipedia.org/wiki/Data_pre-processing)](https://en.wikipedia.org/wiki/Data_pre-processing)
- [https://en.wikipedia.org/wiki/Data_pre-processing](https://en.wikipedia.org/wiki/Data_pre-processing)
11. Forecast Analysis
- [https://en.wikipedia.org/wiki/Forecasting)](https://en.wikipedia.org/wiki/Forecasting)
- [https://en.wikipedia.org/wiki/Forecasting](https://en.wikipedia.org/wiki/Forecasting)
12. ARIMA
- [https://en.wikipedia.org/wiki/Autoregressive_integrated_moving_average](https://en.wikipedia.org/wiki/Autoregressive_integrated_moving_average)
13. Prophet
- [https://facebook.github.io/prophet/](https://facebook.github.io/prophet/)

## Agenda
1. [Presentation](./01.presentation.md) :clock9: **(09:00)**
2. [Introduction](02.introduction.md) **(09:15)**
3. **[Azure Machine Learning Studio](03.azure-machine-learning-studio.md)** :clock10: **(10:00)**
4. [Demo](04.demo.md) :clock1030: **(10:30)**
5. [Where to go next](05.where-to-go-next.md) **(10:50)**
6. [Q&A](06.q&a.md) **(10:55)**
1. [Presentation](./01.presentation.md) :clock0: **(00:00)**
2. [Introduction](02.introduction.md) **(00:15)**
3. **[Azure Machine Learning Studio](03.azure-machine-learning-studio.md)** :clock1: **(01:00)**
4. [Demo](04.demo.md) :clock130: **(01:30)**
5. [Where to go next](05.where-to-go-next.md) **(01:50)**
6. [Q&A](06.q&a.md) **(01:55)**
12 changes: 6 additions & 6 deletions 02.azure-ml/03.azure-machine-learning-studio.md
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Expand Up @@ -195,9 +195,9 @@ JupyterLab is served from the same server and uses the same notebook document fo
- [https://jupyterlab.readthedocs.io/en/stable/getting_started/overview.html](https://jupyterlab.readthedocs.io/en/stable/getting_started/overview.html)

## Agenda
1. [Presentation](./01.presentation.md) :clock9: **(09:00)**
2. [Introduction](02.introduction.md) **(09:15)**
3. [Azure Machine Learning Studio](03.azure-machine-learning-studio.md) :clock10: **(10:00)**
4. **[Demo](04.demo.md)** :clock1030: **(10:30)**
5. [Where to go next](05.where-to-go-next.md) **(10:50)**
6. [Q&A](06.q&a.md) **(10:55)**
1. [Presentation](./01.presentation.md) :clock0: **(00:00)**
2. [Introduction](02.introduction.md) **(00:15)**
3. [Azure Machine Learning Studio](03.azure-machine-learning-studio.md)** :clock1: **(01:00)**
4. **[Demo](04.demo.md) :clock130: **(01:30)**
5. [Where to go next](05.where-to-go-next.md) **(01:50)**
6. [Q&A](06.q&a.md) **(01:55)**
12 changes: 6 additions & 6 deletions 02.azure-ml/04.demo.md
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Expand Up @@ -262,9 +262,9 @@ fig = plot_cross_validation_metric(df_cv, metric='rmse')


## Agenda
1. [Presentation](./01.presentation.md) :clock9: **(09:00)**
2. [Introduction](02.introduction.md) **(09:15)**
3. [Azure Machine Learning Studio](03.azure-machine-learning-studio.md) :clock10: **(10:00)**
4. [Demo](04.demo.md) :clock1030: **(10:30)**
5. **[Where to go next](05.where-to-go-next.md)** **(10:50)**
6. [Q&A](06.q&a.md) **(10:55)**
1. [Presentation](./01.presentation.md) :clock0: **(00:00)**
2. [Introduction](02.introduction.md) **(00:15)**
3. [Azure Machine Learning Studio](03.azure-machine-learning-studio.md)** :clock1: **(01:00)**
4. [Demo](04.demo.md) :clock130: **(01:30)**
5. **[Where to go next](05.where-to-go-next.md) **(01:50)**
6. [Q&A](06.q&a.md) **(01:55)**
12 changes: 6 additions & 6 deletions 02.azure-ml/05.where-to-go-next.md
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Expand Up @@ -92,9 +92,9 @@ Why PyTorch?
- [https://towardsdatascience.com/what-is-pytorch-a84e4559f0e3](https://towardsdatascience.com/what-is-pytorch-a84e4559f0e3)

## Agenda
1. [Presentation](./01.presentation.md) :clock9: **(09:00)**
2. [Introduction](02.introduction.md) **(09:15)**
3. [Azure Machine Learning Studio](03.azure-machine-learning-studio.md) :clock10: **(10:00)**
4. [Demo](04.demo.md) :clock1030: **(10:30)**
5. [Where to go next](05.where-to-go-next.md) **(10:50)**
6. **[Q&A](06.q&a.md)** **(10:55)**
1. [Presentation](./01.presentation.md) :clock0: **(00:00)**
2. [Introduction](02.introduction.md) **(00:15)**
3. [Azure Machine Learning Studio](03.azure-machine-learning-studio.md)** :clock1: **(01:00)**
4. [Demo](04.demo.md) :clock130: **(01:30)**
5. [Where to go next](05.where-to-go-next.md) **(01:50)**
6. **[Q&A](06.q&a.md) **(01:55)**
12 changes: 6 additions & 6 deletions 02.azure-ml/06.q&a.md
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@@ -1,9 +1,9 @@
# Q&A <!-- omit in toc -->

## Agenda
1. [Presentation](./01.presentation.md) :clock9: **(09:00)**
2. [Introduction](02.introduction.md) **(09:15)**
3. [Azure Machine Learning Studio](03.azure-machine-learning-studio.md) :clock10: **(10:00)**
4. [Demo](04.demo.md) :clock1030: **(10:30)**
5. [Where to go next](05.where-to-go-next.md) **(10:50)**
6. [Q&A](06.q&a.md) **(10:55)**
1. [Presentation](./01.presentation.md) :clock0: **(00:00)**
2. [Introduction](02.introduction.md) **(00:15)**
3. [Azure Machine Learning Studio](03.azure-machine-learning-studio.md)** :clock1: **(01:00)**
4. [Demo](04.demo.md) :clock130: **(01:30)**
5. [Where to go next](05.where-to-go-next.md) **(01:50)**
6. [Q&A](06.q&a.md) **(01:55)**