Efficient Model Selection for Deep Neural Networks on Massively Parallel Processing Databases Published 2020-11-17 Download video MP4 360p Recommendations 25:02 Maggy: Asynchronous distributed hyperparameter optimization based on Apache Spark Asynchronous algo… 25:06 Low-end platform profiling with HawkTracer profiler 25:35 GRUB upstream and distros cooperation 30:18 Debugging apps running in Kubernetes An overview of the tooling available 24:07 AI can't cross this line and we don't know why. 31:18 The Story of Shor's Algorithm, Straight From the Source | Peter Shor 25:40 Sharing memories of Python and Rust The story of a lifetime inside Mercurial 29:47 Postmodern strace 18:40 But what is a neural network? | Chapter 1, Deep learning 25:28 Watching Neural Networks Learn 24:34 dav1d: 1 year later dav1d is a fast AV1 decoder 16:47 Why OpenAI's Strawberry paves the way to AGI 24:59 Deterministic debugging with Delve And the state of Delve 3:33:03 Deep Learning: A Crash Course (2018) | SIGGRAPH Courses 35:18 Our road to a k8s/GKE based Closed Build Environment A small journey to an autoscaling build env ba… 25:33 cargo deny Fearlessly update your dependencies 20:33 Gradient descent, how neural networks learn | Chapter 2, Deep learning 21:00 Software distribution: new points of failure In a censored world 1:55:58 Building makemore Part 3: Activations & Gradients, BatchNorm Similar videos 05:45 Neural Network In 5 Minutes | What Is A Neural Network? | How Neural Networks Work | Simplilearn 03:38 Parallel Computing Explained In 3 Minutes 01:01 On the Acceleration of Deep Learning Model Parallelism With Staleness 1:05:38 CMU Neural Nets for NLP 2020 (5): Efficiency Tricks for Neural Nets 10:17 AI/ML, Neural Networks & the future of analytics: Welcome 32:18 Scaling Deep Learning on Databricks 1:04:36 HPC + Ai Machine Learning Models in Scientific Computing More results