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시험 범위
Data Engineering (20%)
Storage
- S3 Data Lakes
- DynamoDB
Transform
- Glue
- Glue ETL
Streaming
- Kinesis
- Kinesis Video Streams
Workflows
- Data Pipelines
- AWS Batch
- Step Function
Exploratory Data Analysis (24%)
Data Science
- Scikit-learn
- Data Distribution
- Trends and Seasonality
Analysis Tools
- Athena
- Quicksight
- EMR
- Apache Spark
Feature Engineering
- Imputation methods
- Outliers
- Binning
- Log Transforms
- One-hot encoding
- Scaling and Normalization
Modeling (36%)
Deep Learning
- Deep Learning crash course (MLP’s, CNN’s, RNN’s)
- Tuning neural networks and regularization techniques
SageMaker
- Architecture
- Built-in algorithms
- Automatic Model tuning
- SageMaker / Spark integration
High-level AI Services
- Comprehend
- Translate
- Polly
- Transcribe
- Lex
- Rekognition
- Personalize / Forecast / Extract
- DeepLens
Evaluating and tuning
- Confusion Matrix
- RMSE
- Precision and Recall
- F1 Score
- ROC / AUC
Machine Learning Implementation and Operations (20%)
SageMaker Operations
- Using containers
- Security with SageMaker
- Choosing instance types
- A/B Testing
- Tensorflow integration
- SageMaker Neo and GreenGrass
- SageMaker Pipes
- Elastic Inference
- Inference Pipelines
2024.08.08 - [AI/자격증] - [AWS Certified Machine Learning Specialty - 2024] 시험 준비에 도움이 되는 사이트들
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