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A Physicists Thoughts On Writing Deep Learning Papers

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Oct 21, 2019
18:49

There's an art form to writing papers and that includes making sure your paper gets read. In today's video I'm going to share my experiences in publishing papers in high profile physics journals, and how that would apply to writing deep learning papers. Learn how to turn deep reinforcement learning papers into code: Get instant access to all my courses, including the new Prioritized Experience Replay course, with my subscription service. $29 a month gives you instant access to 42 hours of instructional content plus access to future updates, added monthly. Discounts available for Udemy students (enrolled longer than 30 days). Just send an email to [email protected] https://www.neuralnet.ai/courses Or, pickup my Udemy courses here: Deep Q Learning: https://www.udemy.com/course/deep-q-learning-from-paper-to-code/?couponCode=DQN-JUNE-22 Actor Critic Methods: https://www.udemy.com/course/actor-critic-methods-from-paper-to-code-with-pytorch/?couponCode=AC-JUNE-22 Curiosity Driven Deep Reinforcement Learning https://www.udemy.com/course/curiosity-driven-deep-reinforcement-learning/?couponCode=ICM-JUNE-22 Natural Language Processing from First Principles: https://www.udemy.com/course/natural-language-processing-from-first-principles/?couponCode=NLP-JUNE-22 Reinforcement Learning Fundamentals https://www.manning.com/livevideo/reinforcement-learning-in-motion Here are some books / courses I recommend (affiliate links): Grokking Deep Learning in Motion: https://bit.ly/3fXHy8W Grokking Deep Learning: https://bit.ly/3yJ14gT Grokking Deep Reinforcement Learning: https://bit.ly/2VNAXql Come hang out on Discord here: https://discord.gg/Zr4VCdv Need personalized tutoring? Help on a programming project? Shoot me an email! [email protected] Website: https://www.neuralnet.ai Github: https://github.com/philtabor Twitter: https://twitter.com/MLWithPhil

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