Embark on a comprehensive journey into the world of machine learning with the Exam Prep MLS-C01: AWS Certified Specialty Machine Learning course by Whizlabs. This course offers a deep dive into the fundamentals of machine learning algorithms and the essential AWS services required for machine learning implementation and operations.
Throughout the course, you'll gain hands-on experience through the AWS Management Console, enabling you to analyze various data gathering techniques, handle missing data, and execute feature extraction and selection using Principal Component Analysis and Variance Thresholds. Additionally, you'll delve into exploratory data analysis, visualizing data for machine learning, and working with AWS services such as Kinesis Data Streams and AWS Glue.
Prepare for the AWS Certified Machine Learning Specialty Certification as you gain the skills and expertise required to excel in the rapidly evolving field of machine learning.
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Embark on a comprehensive learning journey through the modules of Exam Prep MLS-C01: AWS Certified Specialty Machine Learning. Gain expertise in data engineering, exploratory data analysis, modeling, machine learning algorithms, implementation, and operations within AWS environments.
Analyze various data gathering techniques and handle missing data effectively. Implement feature extraction and selection using Principal Component Analysis and Variance Thresholds to enhance your data engineering skills within AWS environments.
Delve into exploratory data analysis, mastering the visualization of data for machine learning. Gain hands-on experience with AWS services such as Kinesis Data Streams and AWS Glue to elevate your expertise in data analysis within AWS environments.
Learn the intricacies of modeling concepts and train machine learning models effectively. Evaluate the performance of machine learning models and implement automatic model tuning to optimize their functionality within AWS environments.
Explore a diverse range of machine learning algorithms, including regression, classification, reinforcement learning, and forecasting. Gain a comprehensive understanding of these algorithms and their practical application within AWS environments.
Design machine learning solutions for performance, availability, scalability, resiliency, and fault tolerance. Implement appropriate machine learning services and features for diverse problem scenarios, and develop machine learning solutions with lab demonstrations to refine your practical skills.
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