W&BWalking through Neural Style Transfer with Weights & BiasesA step-by-step tutorial for understanding Gatys, content and style featuresDec 5, 2019Dec 5, 2019
W&BinWeights & BiasesHow to Use GCP with Weights & BiasesHow to quickly spin up a Notebook instance via the GCP AI Platform and configure Weights and Biases for experiment tracking.Nov 25, 2019Nov 25, 2019
W&BTracking the heartbeat of ML models by exploring gradientsUsing visualizations of gradients to track the heartbeat of ML models, make architectural adjustments, and diagnose problems during…Nov 8, 20191Nov 8, 20191
W&BGenerating Tags from Arvix: An Intro to NLP and Experiment TrackingWalking through critical aspects of an NLP project and how Weights and Biases helped with experiment tracking.Nov 6, 2019Nov 6, 2019
W&BinWeights & BiasesExploring Deep Learning Hyperparameters with Random ForestsUsing random forest feature importance to explore hyperparametersNov 5, 2019Nov 5, 2019
W&BinWeights & BiasesMachine Learning Model Best PracticesLearn how to quickly and efficiently narrow down available models to find those that are most likely to perform best on your problem type.Oct 22, 2019Oct 22, 2019
W&BinWeights & BiasesHyperparameter Optimization using sweeps with W&BSearching through the hyperparameter space and finding the optimal model using sweeps from Weights & Biases.Oct 22, 20191Oct 22, 20191
W&BPyEnv Tutorial for Machine LearningIf you’re doing machine learning and tired of python dependency hell, use pyenv!Oct 22, 20192Oct 22, 20192
W&BinWeights & BiasesNeural Network FundamentalsTraining neural networks can be very confusing. What’s a good learning rate? How many hidden layers should your network have? Is dropout…Oct 21, 2019Oct 21, 2019
W&BinWeights & BiasesMachine Learning Best Practices for Test Driven DevelopmentI sat down with the Latent Space team to talk about best practices around collaboration and managing model iteration. In machine learning…Oct 21, 2019Oct 21, 2019
