Azure ML tutorials is a 10 part series. We will start with an introduction to Azure Machine Learning Studio, subscriptions required to create an account in Azure, and its pricing.
We’ll explore how to import and export data from a variety of sources: HTTP, Azure SQL database, Hadoop Hive query, or Azure Storage Blobs and learn to create workspace and experiment in Azure ML.
We will be showing an end-to-end data exploration science project using one of the data sets and build a data mining strategy and perform preliminary exploration into the dataset using Azure Machine Learning’s dataset module.
We will also cover summary statistics and data transformation, and build a machine learning model in Azure ML.
In this course, you will:
- Creating an Azure ML account
- Creating workspace and experiments in Azure
- Importing and exporting data into Azure ML
- Data mining strategy and data exploration techniques using Azure ML
- Building a predictive model and test the accuracy of the model
1. Getting Started
- What is Azure Machine Learning?
- Subscription and Workspaces
2. Importing/Exporting Data
- Import and Export Data, Modules, Experiments
3. Data Exploration
- Data Exploration
- Renaming Columns and Replicating Data
- Joining Datasets
- Dropping & Selecting ColumnsPage
4. Data Cleaning
- Summary Statistics & Cleaning Missing Data
5. Data Transformation
- Splitting Data & Categorical Casting
- Building a Machine Learning Model