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Hands-On Deep Learning Deep Dive | Getting Started with Mathematical Concepts, Algorithms, Neural Networks & More
Hands-On Deep Learning Deep Dive is a fast-paced, hands-on four day course that teaches students the modern skills and concepts that reside in the mathematical side of ML / DL, providing attendees with a solid platform for next-level, continued learning in this space based on role or goal.
Course Overview
This in an intermediate-level course is geared for experienced developers or others (with prior Python experience) intending to start using learning about and working with machine learning algorithms, machine learning, deep learning fundamentals and concepts. . Attendees should be experienced developers who are comfortable with Python programming. Students should also be able to navigate Linux command line, and who have basic knowledge of Linux editors (such as VI / nano) for editing code.
4176 S Plaza Trail
Suite 207
Virginia Beach, VA 23452
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Learning Objectives
This “skills-centric” course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern “on-the-job” modern machine learning experience into every classroom and hands-on project. Students will learn about and work with: Mathematical Concepts Machine Learning Concepts Machine Learning Algorithms Overview Deep Learning Deep Neural Networks
Framework Connections
The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):
Work Roles
Feedback
If you would like to provide feedback on this course, please e-mail the NICCS team at NICCS@mail.cisa.dhs.gov. Please keep in mind that NICCS does not own this course or accept payment for course entry. If you have questions related to the details of this course, such as cost, prerequisites, how to register, etc., please contact the course training provider directly. You can find course training provider contact information by following the link that says “Visit course page for more information...” on this page.