This Keras test evaluates candidates' proficiency in designing model architectures, understanding Keras framework, and applying deep learning principles. It covers TensorBoard integration, data structures, algorithms, documentation, best practices, and transfer learning with pretrained models.
This Keras test is designed to assess candidates' expertise in model architecture design, a comprehensive understanding of the Keras framework, and foundational knowledge of deep learning principles. It evaluates the ability to integrate TensorBoard for model visualization and performance tracking, as well as proficiency in data structures and algorithms. The test also covers documentation skills, adherence to best practices, and the application of transfer learning using pretrained models. Ideal for roles requiring a deep understanding of Keras and its application in real-world scenarios, this assessment ensures candidates are well-versed in the essential aspects of Keras and deep learning.
This assessment is suitable for roles such as Machine Learning Engineer, Deep Learning Specialist, AI Developer, Data Scientist, and Software Engineer focusing on AI and machine learning projects.
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Access to Real-world, work like Assessments - Projects, DevOps, Machine Learning, Subjective (AI Evaluated), Video (Technical Knowledge), Video (Communication Skill), Whiteboarding (AI Evaluated)
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Access to Objective Way of Assessments - MCQs, Checboxes, Fill in the blanks, Subjective (Manually Scored), File Upload (Manually Scored)
Access to Practice Way of Assessments - Programming, Debugging, Database, Data Science,
Access to Real-world, work like Assessments - Projects, DevOps, Machine Learning, Subjective (AI Evaluated), Video (Technical Knowledge), Video (Communication Skill), Whiteboarding (AI Evaluated)
Assessment Design consultation services according to Curriculum, Training or Learning Paths