Applications of Machine Learning methods have significantly contributed to the development of biomedical research and drug discovery. In this talk Nazim Medzhidov and Romeo Cozac focus on 1) understanding the types of biological/chemical data available and challenges in biomedical research, 2) providing examples on how ML approaches using biological/chemical data are used to address complex … Continue reading MACHINE LEARNING IN LIFE SCIENCE RESEARCH & DRUG DISCOVERY
AI, Machine Learning and Deep Learning this month, at a glance.
In this online RL series we will cover "Reinforcement learning: An introduction" by Richard Sutton and Andrew Barto.
This is part of the CNN Architectures series by Dimitris Katsios. Find all CNN Architectures online: Notebooks: MLT GitHubVideo tutorials: YouTubeSupport MLT on Patreon ShuffleNet We will use the tensorflow.keras Functional API to build ShuffleNet from the original paper: “ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices” by Xiangyu Zhang, Xinyu Zhou, Mengxiao Lin, Jian Sun. ShuffleNet: Video tutorial … Continue reading CNN ARCHITECTURES: SHUFFLENET
The most important happenings in Machine Learning, Deep Learning and AI this month, at a glance.
We are excited to announce our Fastbook Sessions with Sanyam Bhutani.This will be a series of 2-hour weekly study sessions dedicated to going through the book, "Deep Learning for Coders with fastai and PyTorch: AI applications Without a PhD" written by the creators of the fast.ai course. The authors of the course were kind enough … Continue reading THE FASTBOOK SESSIONS