Video: AWS Certified Machine Learning – Specialty
Domain 1 Data Engineering
Domain 2 Exploratory Data Analysis
Domain 3 Modeling
- 3.1 Frame the business problem
- 3.2 Select the appropriate models
- 3.3 Train the models
- Gradient Descent
- Serialization formats: JSON and Protobuf
- What Is Overfitting in Machine Learning?
- Machine Learning Overfitting
- Train Your ML Models Accurately with Amazon SageMaker
- Machine Learning with Containers and Amazon SageMaker
- Introduction to Amazon EC2 P3 Instances
- Machine Learning Models with TensorFlow Using Amazon SageMaker
- 3.4 Tune the models
- 3.5 Evaluate the models
Domain 4 Machine Learning Implementation and Operations
- 4.1 Build machine learning solutions for performance, availability, scalability, resiliency, and fault tolerance.
- 4.2 Recommend and implement the appropriate machine learning services and features for a given problem.
- 4.3 Apply basic AWS security practices to machine learning solutions.
- 4.4 Deploy and operationalize machine learning solutions.
Whizlab’s AWS Certified Machine Learning Specialty practice exams
Whizlab’s AWS Certified Machine Learning Specialty Practice tests are designed by experts to simulate the real exam scenario. The questions are based on the exam syllabus outlined by official documentation. These practice tests are provided to the candidates to gain more confidence in exam preparation and self-evaluate them against the exam content.
Practice test content
- Free Practice test – 15 questions
- Practice test 1 – 65 questions
- Practice test 2 – 65 questions
- Practice test 3 – 65 questions
Section test content
- Core ML Concepts – 10 questions
- Data Engineering – 11 questions
- Exploratory Data Analysis – 13 questions
- Modeling – 15 questions
- Machine Learning Implementation and Operations – 12 questions