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Machine Learning: Hands On
Duration: 5 Days Code: BDT189 Category: Data EngineeringOver the past few years, Big Data and its analysis have grown exponentially and changed the way businesses operate.
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Byte-Sized ML Basic Series: Machine Learning Model Optimization
Duration: 90 Minutes Code: BDT183 Category:A short session to review techniques for optimizing machine learning model performance.
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Byte-Sized ML Basic Series: Machine Learning Model Deployment
Duration: 90 Minutes Code: BDT182 Category:A short session exploring different ways to deploy machine learning models and some of the tools involved.
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Byte-Sized ML Series: Machine Learning Introduction
Duration: 90 Minutes Code: BDT177 Category:This concise session will provide a clear overview of machine learning.
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Introduction to Statistical Analysis with R
Duration: 2 Full Days Or 4 Half Days Code: BDT154 Category:This course will provide an introduction to statistical analysis and data modeling.
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Jupyter Notebook for Effective Data Analysis and Collaboration
Duration: Half Day Code: BDT153 Category:This course will help you to become familiar with the popular Jupyter Notebook environment and all of its features.
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Byte-Sized Deep Learning Series: Applied Deep Learning for Natural Language Understanding
Duration: 90-minute Code: BDT151 Category:This 90-minute session will explore the application of deep learning models known as transformers to solve common natural language understanding tasks.
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Byte-Sized Deep Learning Series: Understanding Language
Duration: 90 minutes Code: BDT151 Category:This 90-minute session will explore the use of deep learning and the role of recurrent neural networks in language understanding.
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Byte-Sized Deep Learning Series: Image Recognition
Duration: 90 minutes Code: BDT149 Category:This course is for those who are interested in gaining an understanding of how deep learning is used to recognize and classify images
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Byte-Sized Deep Learning Series: Introducing Neural Networks
Duration: 90 minutes Code: BDT148 Category:This course is for those who would like to understand how to apply deep learning to common natural language understanding tasks.