AWS Certified Machine Learning Specialty 2020 – Hands On!
Learn SageMaker, feature engineering, model tuning, and the AWS machine learning ecosystem. Be prepared for the exam!
Created by Sundog Education by Frank Kane, Stephane Maarek | AWS Certified Solutions Architect & Developer | 9 hours on-demand video course
[ v2020: The course was recorded in October 2019 and will be kept up-to-date all of 2020. Happy learning! ] Nervous about passing the AWS Certified Machine Learning – Specialty exam (MLS-C01)? You should be! There’s no doubt it’s one of the most difficult and coveted AWS certifications. A deep knowledge of AWS and SageMaker isn’t enough to pass this one – you also need deep knowledge of machine learning, and the nuances of feature engineering and model tuning that generally aren’t taught in books or classrooms. You just can’t prepare enough for this one.
What you’ll learn
- What to expect on the AWS Certified Machine Learning Specialty exam
- Amazon SageMaker’s built-in machine learning algorithms (XGBoost, BlazingText, Object Detection, etc.)
- Feature engineering techniques, including imputation, outliers, binning, and normalization
- High-level ML services: Comprehend, Translate, Polly, Transcribe, Lex, Rekognition, and more
- Data engineering with S3, Glue, Kinesis, and DynamoDB
- Exploratory data analysis with scikit_learn, Athena, Apache Spark, and EMR
- Deep learning and hyperparameter tuning of deep neural networks
- Automatic model tuning and operations with SageMaker
- L1 and L2 regularization
- Applying security best practices to machine learning pipelines
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