Machine Learning Azure Decision Tree Score-2

Azure Machine Learning Experiments/Data Flows

This is a picture series to depict machine learning Azure algorithms & solution as part of practice. It is intended to give a quick overview of the components in Azure for machine learning solutions.

You can understand this better after going through basic machine learning development process. But if you do not, you may still give it a go.

The first goal of machine learning is to train models. So, below are some models I trained.

Machine Learning Azure Trained Models
Machine Learning Azure Trained Models

Creating models become easy with proper data cleaning & transformation. Below is an example.

Machine Learning Azure Data Cleaning-1
Machine Learning Azure Data Cleaning-1
Machine Learning Azure Data Cleaning-2
Machine Learning Azure Data Cleaning-2

These models were exposed as web service in azure, which allows to test any new data.

Machine Learning Azure Web Services
Machine Learning Azure Web Services

Here’s peek at data sets used.

Machine Learning Azure Datasets
Machine Learning Azure Datasets

Below are some experiments which I developed. In fact, Machine Learning modelling is possible using experiments in Azure.

Machine Learning Azure Experiments By BSOHAL
Machine Learning Azure Experiments By BSOHAL

It would be interesting to see what these experiments are.

Machine Learning Azure Logistic Regression Train
Machine Learning Azure Logistic Regression Train
Machine Learning Azure Logistic Regression Score
Machine Learning Azure Logistic Regression Score
Machine Learning Azure Linear Regression Train
Machine Learning Azure Linear Regression Train
Machine Learning Azure Linear Regression Score
Machine Learning Azure Linear Regression Score
Machine Learning Azure Decision Tree Train-1
Machine Learning Azure Decision Tree Train-1
Machine Learning Azure Decision Tree Train-2
Machine Learning Azure Decision Tree Train-2
Machine Learning Azure Decision Tree Score-1
Machine Learning Azure Decision Tree Score-1
Machine Learning Azure Decision Tree Score-2
Machine Learning Azure Decision Tree Score-2
Machine Learning Azure Decision Forest
Machine Learning Azure Decision Forest

The heart of Machine Learning in Azure is creating these experiments or data flows. And these allow all processing logic, like calling Python or R scripts, SQL transformation, data transformation, data format conversions, applying math or string functions, Feature Selection, Split/Join data, normalize data, editing metadata, Statistical functions, Text Analytics, Time Series & finally train, score and evaluate models based on Machine Learning Algorithms.

Finally, if you would like to get to Azure, you can register here: https://studio.azureml.net/

More articles can be found here: https://www.etechaas.com/tag/machine-learning/

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