Applications Big Data and Analytics IT Management Why Machine Learning Projects Fail – and How to Make Sure They Don’t The first step to a successful ML project is to understand that these ...

Use modern machine learning tools and python libraries. Explain how to deal with linearly-inseparable data. Compare logistic regression’s strengths and weaknesses. Explain what decision tree is & how ...

For those needing robust ELT, data science, and machine learning features within a data lake/data warehouse framework, Databricks is the winner. Azure ML wins for those just wanting to add ML to ...