- Why are Machine Learning Projects so Hard to Manage? - Feb 3, 2020.
What makes deploying a machine learning project so difficult? Is it the expectations? The people? The tech? There are common threads to these challenges, and best practices exist to deal with them.
Deployment, Kaggle, Lukas Biewald, Machine Learning, Project Fail, Training Data
- How to Build a Machine Learning Team When You Are Not Google or Facebook - Nov 28, 2018.
If you don’t have a clear application for machine learning, you’re going to regret your investment. We provide tips on how to go about setting up your machine learning team - no matter the size of your business.
Data Science Team, Google, Lukas Biewald, Machine Learning, Team
- What we can learn from AI mistakes - Dec 19, 2016.
Because of recent innovations and research in AI, we have seen AI performing best in some very important tasks and even worst in even simple tasks. So the question is, Why is it that AI can look so brilliant and so stupid at the same time?
AI, AlphaGo, CrowdFlower, Lukas Biewald, Mistakes, Self-Driving Car, TensorFlow
- The Machine Learning Problem of The Next Decade - Feb 26, 2016.
How can businesses integrate imperfect machine-learning algorithms into their workflow?
Pages: 1 2
Accuracy, Cars, CrowdFlower, Kaggle, Lukas Biewald, Machine Learning, Prediction, Self-Driving Car
- Rich Data Summit Takeaways - Oct 19, 2015.
Data scientists get excited about algorithms. But nearly all time spent working with data involves acquiring, pipelining, annotating and cleaning it. At the Rich Data Summit in SF, data's dirty work took center stage.
CrowdFlower, Data Cleaning, Lukas Biewald, Nate Silver, Zachary Lipton
