No-Code Machine Learning Using Amazon AWS SageMaker Canvas - Getting Datasets for Practice

The video tutorial introduces machine learning and emphasizes the importance of selecting the right datasets. It explores various resources for obtaining datasets, including AWS Open Data Registry, Google Dataset Search, Microsoft Research, Bright Data, Kaggle, and UCI Machine Learning Repository. Each platform offers unique datasets suitable for different machine learning projects, helping learners build models and gain confidence in the field.

What is the first step mentioned for getting started with machine learning?

• Understanding algorithms

• Finding the right dataset

• Learning programming languages

• Setting up a cloud environment

Which platform is highlighted as a large repository of datasets on AWS?

• Bright Data

• Registry of Open Data on AWS

• Microsoft Research Open Data

• Google Dataset Search

What type of datasets can be found in Microsoft Research Open Data?

• NLP, computer vision, and domain-specific sciences

• Social media and marketing

• E-commerce and finance

• Weather and climate

Which platform is known for hosting machine learning competitions?

• Kaggle

• Google Dataset Search

• Bright Data

• UCI Machine Learning Repository

What is a common feature of datasets available on Kaggle?

• They are primarily for social sciences

• They are only available for purchase

• They are exclusive to academic institutions

• They are free and can be used for competitions