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Build and End to End ML Projects on AWS SageMaker

Name: Build and End to End ML Projects on AWS SageMaker
Price: 19.99 USD
Availability: InStock

About this course

Unlock the full potential of AWS SageMaker and become a machine learning and data science expert with our comprehensive "Mastering AWS SageMaker" course. Whether you are a beginner looking to explore the world of machine learning or a seasoned professional seeking to enhance your skills, this course is your key to mastering the AWS SageMaker platform.Course Highlights:Fundamentals of AWS SageMaker: Begin your journey by understanding the core concepts of AWS SageMaker, cloud computing, and machine learning. You'll gain insights into the key components of SageMaker and how they fit into the machine-learning workflow.Data Preprocessing and Feature Engineering: Learn how to prepare and preprocess data for machine learning, an essential step in building robust models. Explore feature engineering techniques to extract meaningful insights from your data.Model Building and Training: Dive into the heart of machine learning by creating, training, and fine-tuning models on SageMaker. Understand various algorithms, optimization strategies, and hyperparameter tuning for better model performance.Deploying Models: Discover how to deploy your machine learning models into production with SageMaker. You'll explore best practices for deploying models at scale, ensuring high availability, and achieving optimal performance.Automated Machine Learning (AutoML): Uncover the power of AutoML with SageMaker, allowing you to automate many aspects of the machine learning process, saving you time and effort in model development.MLOps and Model Monitoring: Learn how to implement MLOps best practices and set up automated model monitoring to ensure your deployed models remain accurate and reliable.Advanced Topics: Delve into advanced topics such as natural language processing (NLP), computer

62/100

CourseAsk score

What the provider tells you: 38/45
Who stands behind it: 8/35
How complete the listing is: 16/20

Scores how much the provider publishes and who stands behind it — not how well it is taught.

What you'll learn

Understand the core concepts of AWS SageMaker
Perform data preprocessing and feature engineering for machine learning
Build, train, and fine-tune machine learning models
Deploy machine learning models into production
Implement AutoML techniques using SageMaker
Apply MLOps best practices for model monitoring

Machine Learning Cloud Computing #model deployment #aws #machine learning #mlops #model monitoring #cloud computing #computer vision #natural language processing #feature engineering #hyperparameter tuning #model building #automated machine learning #data preprocessing #sagemaker

$19.99

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