Tagged “Machine Learning”
Tagged “Machine Learning”
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Module AWS Certified Machine Learning - Specialty
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Getting Started with ML Python Quickstart
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Common Terms in ML and AI
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An Introduction to ML and AI Terms
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Getting Started with Machine Learning
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AWS Certified Machine Learning - Specialty (MLS-C01) Exam Guide
Discover the essential steps to prepare for the AWS Certified Machine Learning - Specialty exam, from mastering ML concepts to selecting the right AWS services. This guide offers a comprehensive roadmap for candidates aiming to certify their expertise in designing, implementing, and managing ML solutions on AWS.
Explore this guide on getting started with machine learning in Python, covering essential libraries like NumPy, Pandas, Matplotlib, Seaborn, Bokeh, and Scikit-learn for beginners.
A concise glossary of common terms encountered in the realm of Machine Learning (ML) and Artificial Intelligence (AI), including Algorithm, Supervised Learning, Unsupervised Learning, Reinforcement Learning, Epoch, Overfitting, Backpropagation, Activation Function, Loss Function, Gradient Descent, Convolutional Neural Networks, Recurrent Neural Networks, Transfer Learning, Bias in AI, and Generative Adversarial Networks.
This concise guide introduces key terms and concepts in the field of Artificial Intelligence (AI) and Machine Learning (ML). It explains the broader concept of AI, subsets like Machine Learning and Deep Learning, Neural Networks, Large Language Models, Training, and Datasets.
A comprehensive guide to starting with Machine Learning. It covers the introduction to AI and Machine Learning, basic terminologies, understanding data, the Machine Learning process, common algorithms, introduction to Neural Networks and Deep Learning, tools and libraries, hands-on projects, evaluation metrics, and ethical considerations.
This guide provides a comprehensive overview of the AWS Certified Machine Learning - Specialty (MLS-C01) exam. It includes details on the exam's structure, content domains, task statements, and the relevant AWS services and features. It also includes an appendix with additional resources.
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