Sale Price Prediction using Azure Machine Learning Studio with Excel API integration that help you predict house prices based on machine learning algorithm (K-means Clustering).
1. Create a Machine Learning Model with Azure Machine Learning Studio - Explore and visualize datasets with python in jupyter notebooks. - Use Zscore Transformation method to Normalize data. - Train a regression model (supervised learning) - Evaluate Model
2. Publish trained model to a webservice and use it to predict labels from new feature data. - Deploy the web service - Consume the web service with excel
3. Train a classification model (supervised learning) in Azure Machine learning studio
4. Train a clustering model (Unsupervised learning) - copy an existing training experiment from the Azure AI Gallery and run it to train a K-Means clustering model that segments specific customers into clusters based on similarities in their features
Published Links to my Azure Machine Learning Environment https://gallery.azure.ai/Experiment/Lemonade-Training-28 https://gallery.azure.ai/Experiment/Predict-Lemonade-Sales-19 https://gallery.azure.ai/Experiment/Lemonade-Clustering-Customers-6