Amazon Web Service using MLops - IM
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.png&name=Amazon Web Service using MLops - IM&caption=undefined&description=<p><span style="color: rgb(55, 65, 81);">Amazon Web Services (AWS) provides a range of services and tools to support Machine Learning Operations (MLOps), the practices that aim to streamline the deployment, management, and scaling of machine learning models. AWS offers a comprehensive set of services for building, training, deploying, and managing machine learning models, and several of these services are key components of an MLOps pipeline. Here are some AWS services commonly used in MLOps.</span></p><p><br></p><p><strong>Part - 1: Introduction to Amazon web services</strong></p><p>Day 1 - aws Introduction, account creation</p><p>Day 2 - aws cloud essentials 1 - Virtual machines (EC2), ELB, EBS</p><p>Day 3 - aws cloud essentials 2 - AWS Lambda, docker container, ECS, EKS</p><p>Day 4 - aws cloud Essentials 3 - RDS, DynamoDB, S3</p><p><strong>Part - 2: Machine learning</strong></p><p>Day 5 - Introduction to machine learning, ML with AWS Sagemaker</p><p>Day 6 - Data collection, Pandas for machine learning</p><p>Day 7 - Data Engineering with (aws glue, glue ETL, Athena)</p><p>Day 8 - Numpy for machine learning</p><p>Day 9 - Matplotlib, Seaborn for machine learning</p><p>Dat 10 - aws data wrangler</p><p>Day 11 - Feature Scaling, encoding, handling null values</p><p>Day 12 - Outlier detection & handling, feature selection, train test split</p><p>Day 13 - Data preprocessing with SageMaker’s Scikit-Learn Container</p><p>Day 14 - Machine learning Modeling, model evaluation</p><p>Day 15 - aws Sagemaker built-in Algorithms for ML</p><p>Day 16 - Machine learning project - classification - Vehicle insurance claim fraud detection</p><p>Day 17 - Machine learning project - Regression - Abalone age prediction</p><p>Day 18 - AWS Sagemaker canvas, autopilot</p><p>Day 19 - Deep learning introduction</p><p>Day 20 - CNN project - Dog / Cat identification project</p><p>Day 21 - RNN, NLP basics</p><p>Day 22 - NLP project - Clothing - e-commerce review project</p><p><strong>Part - 3: Deployment</strong></p><p>Day 23 - Version control with Git & Github</p><p>Day 24 - CI/CD with Github</p><p>Day 25 - Deploying model with aws sagemaker</p><p>Day 26 - CI/CD with sagemaker pipeline</p><p>Day 27 - Census income prediction project with deployment</p><p>Day 28 - Music recommender system project with deployment</p><p>Day 29 - AWS AI services - Amazon Rekognition, Comprehend, Polly</p><p>Day 30 - AWS AI services - Lex, Transcribe, Textract</p><p><br></p><p>Amazon web service using MLops course will be added to the LMS Portal, we will send notify to your registered mail. If you didn't receive according login credentials.</p>&redirect_uri=http://www.facebook.com)
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Amazon Web Service using MLops - IM
₹
1,500
₹
2,999
50% off
Exclusive of taxes
Share this
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Amazon Web Services (AWS) provides a range of services and tools to support Machine Learning Operations (MLOps), the practices that aim to streamline the deployment, management, and scaling of machine learning models. AWS offers a comprehensive set of service
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