@@ -44,27 +44,27 @@ Download or clone this repo and open the `machine-learning` folder in Visual Stu
44
44
45
45
### Getting Started Series
46
46
47
- | # | Topic | Notebook Link |
48
- | ---| --------------------------------------------| -----------------------|
49
- 1 | Intro to Machine Learning | [ 01 Notebook] ( https://ntbk.io/ml-01-intro )
50
- 2 | Data Prep and Feature Engineering | [ 02 Notebook] ( https://ntbk.io/ml-02-data )
51
- 3 | Training and AutoML | [ 03 Notebook] ( https://ntbk.io/ml-03-training )
52
- 4 | Model Evaluation | [ 04 Notebook] ( https://ntbk.io/ml-04-evaluation )
47
+ | # | Topic | VS Notebook Link | Github Link |
48
+ | ---| --------------------------------------------| ------------------------------------------------ | ------------- |
49
+ 1 | Intro to Machine Learning | [ 01 Notebook] ( https://ntbk.io/ml-01-intro ) | [ 01 Notebook ] ( https://github.com/dotnet/csharp-notebooks/blob/main/machine-learning/01-Intro%20to%20Machine%20Learning.ipynb )
50
+ 2 | Data Prep and Feature Engineering | [ 02 Notebook] ( https://ntbk.io/ml-02-data ) | [ 02 Notebook ] ( https://github.com/dotnet/csharp-notebooks/blob/main/machine-learning/02-Data%20Preparation%20and%20Feature%20Engineering.ipynb )
51
+ 3 | Training and AutoML | [ 03 Notebook] ( https://ntbk.io/ml-03-training ) | [ 03 Notebook ] ( https://github.com/dotnet/csharp-notebooks/blob/main/machine-learning/03-Training%20and%20AutoML.ipynb )
52
+ 4 | Model Evaluation | [ 04 Notebook] ( https://ntbk.io/ml-04-evaluation ) | [ 04 Notebook ] ( https://github.com/dotnet/csharp-notebooks/blob/main/machine-learning/04-Model%20Evaluation.ipynb )
53
53
54
54
### End to End (E2E) Notebooks - examples of the entire ML process.
55
- | # | Topic | Notebook Link |
56
- | ---| --------------------------------------------| -----------------------|
57
- E2E | Classification using AutoML (Iris Dataset) | [ Iris E2E AutoML] ( https://ntbk.io/ml-e2e-iris )
58
- E2E | Forecasting using Regression (Luna Dataset)| [ Luna E2E Regression] ( https://ntbk.io/ml-e2e-luna-regression )
59
- E2E | Forecasting using SSA (Luna Dataset) | [ Luna E2E SSA] ( https://ntbk.io/ml-e2e-luna-ssa )
60
- E2E | Regression using AutoML (Taxi Dataset) | [ Taxi E2E AutoML] ( https://ntbk.io/ml-e2e-taxi )
55
+ | # | Topic | VS Notebook Link | Github Link |
56
+ | ---| --------------------------------------------| -------------------------------------------------------------- | ------------- |
57
+ E2E | Classification using AutoML (Iris Dataset) | [ Iris E2E AutoML] ( https://ntbk.io/ml-e2e-iris ) | [ Iris E2E AutoML ] ( https://github.com/dotnet/csharp-notebooks/blob/main/machine-learning/E2E-Classification%20with%20Iris%20Dataset.ipynb )
58
+ E2E | Forecasting using Regression (Luna Dataset)| [ Luna E2E Regression] ( https://ntbk.io/ml-e2e-luna-regression ) | [ Luna E2E Regression ] ( https://github.com/dotnet/csharp-notebooks/blob/main/machine-learning/E2E-Forecasting%20using%20Regression%20with%20Luna%20Dataset.ipynb )
59
+ E2E | Forecasting using SSA (Luna Dataset) | [ Luna E2E SSA] ( https://ntbk.io/ml-e2e-luna-ssa ) | [ Luna E2E SSA ] ( https://github.com/dotnet/csharp-notebooks/blob/main/machine-learning/E2E-Forecasting%20using%20SSA%20with%20Luna%20Dataset.ipynb )
60
+ E2E | Regression using AutoML (Taxi Dataset) | [ Taxi E2E AutoML] ( https://ntbk.io/ml-e2e-taxi ) | [ Taxi E2E AutoML ] ( https://github.com/dotnet/csharp-notebooks/blob/main/machine-learning/E2E-Regression%20with%20Taxi%20Dataset.ipynb )
61
61
62
62
### Reference Notebooks
63
- | # | Topic | Notebook Link |
64
- | ---| --------------------------------------------| -----------------------|
65
- REF | Data Processing with DataFrame |[ Data Frame] ( https://ntbk.io/ml-ref-data-frame )
66
- REF | Graphs and Visualizations |[ Visualizations] ( https://ntbk.io/ml-ref-visualizations )
67
- REF | Kaggle Competitions (Titanic Dataset) |[ Kaggle] ( https://ntbk.io/ml-ref-kaggle-titanic )
63
+ | # | Topic | VS Notebook Link | Github Link |
64
+ | ---| --------------------------------------------| ------------------------------------------------------- | ------------- |
65
+ REF | Data Processing with DataFrame |[ Data Frame] ( https://ntbk.io/ml-ref-data-frame ) | [ Data Frame ] ( https://github.com/dotnet/csharp-notebooks/blob/main/machine-learning/REF-Data%20Processing%20with%20DataFrame.ipynb )
66
+ REF | Graphs and Visualizations |[ Visualizations] ( https://ntbk.io/ml-ref-visualizations ) | [ Visualizations ] ( https://github.com/dotnet/csharp-notebooks/blob/main/machine-learning/REF-Graphs%20and%20Visualizations.ipynb )
67
+ REF | Kaggle Competitions (Titanic Dataset) |[ Kaggle] ( https://ntbk.io/ml-ref-kaggle-titanic ) | [ Kaggle ] ( https://github.com/dotnet/csharp-notebooks/blob/main/machine-learning/REF-Kaggle%20with%20Titanic%20Dataset.ipynb )
68
68
69
69
## .NET Foundation
70
70
0 commit comments