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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This course provides the latest concepts, tools and techniques to build and influence the development of a successful data science and machine learning capability. Delivered through an interactive approach utilising the latest tools, participants of this course are exposed to basic techniques
This course explores a collaborative project between the UTS Data Science Institute and Sydney Trains. The objective of the project was to develop a timetable robustness evaluation model using analytical/statistical methods, or machine learning techniques.
Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars
Perform Cloud Data Science with Azure Machine Learning course is offered by Wardy IT Solutions. As a Microsoft Partner we’ve been awarded with the Silver Learning competency. Every training session we run is taught by a Microsoft Certified Trainer.
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.
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