AWS Machine Learning Specialty
Everythiing you need to pass the AWS Machine Learning Specialty
AWS Certified Machine Learning Specialty Practice Exam Test Sets.
Use these 125 questions and answers with explanations help to you for preparation and pass the AWS Certified Machine Learning Specialty Practice Exams, You can take the exam as many times as you need to the master of AWS Certified Machine Learning Specialty Exams, Thank You.
AWS Certified Machine Learning – Specialty
About AWS Certified Machine Learning – Specialty Practice Exam
AWS Certified Machine Learning – Specialty certification exam is intended for individuals who perform a development or data science role. It validates a candidate’s ability to design, implement, deploy, and maintain machine learning (ML) solutions for given business problems.
Skills Validated by the Certification
- Select and justify the appropriate ML approach for a given business problem
- Identify appropriate AWS services to implement ML solutions
- Design and implement scalable, cost-optimized, reliable, and secure ML solutions
Recommended AWS Knowledge
Successful candidate likely has one to two years of hands-on experience developing, architecting, or running ML/deep learning workloads on the AWS Cloud, along with –
- Ability to express the intuition behind basic ML algorithms
- Experience performing basic hyperparameter optimization
- Experience with ML and deep learning frameworks
- Ability to follow model-training best practices
- Ability to follow deployment and operational best practices
Course outline for AWS Certified Machine Learning – Specialty Practice Exam
Domain 1: Data Engineering
1.1 Create data repositories for machine learning.
1.2 Identify and implement a data-ingestion solution.
1.3 Identify and implement a data-transformation solution.
Domain 2: Exploratory Data Analysis
2.1 Sanitize and prepare data for modeling.
2.2 Perform feature engineering.
2.3 Analyze and visualize data for machine learning.
Domain 3: Modeling
3.1 Frame business problems as machine learning problems.
3.2 Select the appropriate model(s) for a given machine learning problem.
3.3 Train machine learning models.
3.4 Perform hyperparameter optimization.
3.5 Evaluate machine learning 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.
We are experts in our respective fields of area. These trainings and quizzes are designed to make you successful in passing the exams.
We have developed industry agnostic training. The training is applicable for any industry including:-
- Aerospace | Automotive | Consumer products | Electronics | Agribusiness,
- Education, | Food and Food Services, | Financial and Insurance Services,
- Government, | Healthcare (Medical and Pharmaceutical),
- Manufacturing, | Industrial equipment, | Non-Profit, | Process industries,
- Golf Courses, Dentists, Doctors, Car Dealerships, Lawyers etc...
if you have any questions, please contact us.