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2. Exploratory Data Analysis

Before building machine learning models, AWS-Certified-Machine-Learning-Specialty-MLS-C01 Exam Dumps  data scientists must analyze and explore the data to understand its characteristics and find patterns. This domain covers data visualization, statistical analysis, and the use of tools like Jupyter Notebooks and SageMaker for exploratory analysis.

3. Modeling

Modeling is the core of machine learning, and this domain tests your knowledge of various machine learning algorithms and techniques. AWS-Certified-Machine-Learning-Specialty-MLS-C01 Exam Dumps PDF You should be familiar with supervised and unsupervised learning, regression models, classification models, and neural networks, among others. AWS tools such as SageMaker and AWS Lambda are crucial in this domain for creating, training, and deploying models.

4. Machine Learning Implementation and Operations

This domain tests your ability to deploy machine learning models at scale, monitor them, and optimize their performance. It covers topics like model deployment using SageMaker, batch and real-time inference, model versioning, and the use of CloudWatch for monitoring.

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