Why are Machine Learning Projects So Hard to Manage?
I’ve watched lots of companies attempt to deploy machine learning — some succeed wildly and some fail spectacularly. One constant is that machine learning teams have a hard time setting goals and setting expectations. This talk will give some examples of how teams fail and recommendations for everyone from executives to researchers to make their machine learning projects work better.
Lukas Biewald is a co-founder and CEO of Weights and Biases which builds performance and visualization tools for machine learning teams and practitioners. Lukas also cofounded Figure Eight (formerly CrowdFlower) — a human in the loop platform that transforms unstructured text, image, audio, and video data into customized high quality training data. Prior to co-founding Weights and Biases and CrowdFlower, Biewald was a Senior Scientist and Manager within the Ranking and Management Team at Powerset, a natural language search technology company later acquired by Microsoft. From 2005 to 2006, Lukas also led the Search Relevance Team for Yahoo! Japan. Weights & Biases (wandb) helps you track your machine learning experiments. Easily add our package, wandb, to your model script to log hyperparameters and output metrics from your runs, explore model architectures, and compare results. Once you install our library we make it easy to share your results with colleagues and your future self.