This Machine Learning with Sagemaker (AWS) course intended for data scientists and software engineers
This Machine Learning with Sagemaker (AWS) course intended for data scientists and software engineers. The course combines an overview and understanding of Machine Learning concepts with specific implementation in SageMaker. In addition, it brings in other tools outside of SageMaker when required.
Machine Learning (ML) is the killer app for Big Data. Amazon Machine Learning brings the power of ML to a regular programmer and provides ML as a service. However, to use ML effectively, one needs to understand the models used and how to utilize them on Amazon.
For each machine learning concept, we first discuss the foundations, its applicability and limitations. Then we explain the implementation and use, and specific use cases.
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In all fields of research we are being confronted with a deluge of data; data that needs cleaning and transformation to be used in further analysis. This webinar demonstrates the effective use of programming tools for an initial analysis of COVID-19 datasets, with examples using both R and Python.
This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
TensorFlow Extended (TFX) is an end-to-end platform for deploying production ML pipelines. This instructor-led, live training (online or onsite) is aimed at data scientists who wish to go from training a single ML model to deploying many ML models to production.
This training course is for people that would like to apply basic Machine Learning techniques in practical applications.
This course covers an introduction to machine learning, helping candidates to acquire the essential knowledge and skills needed to understand and apply different machine learning techniques.
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