Meet the Keynote Speakers at Nebraska.Code() this July! @smasis will present on #AI and @housecor will discuss key lifestyle systems that profoundly impact our #career potential. nebraskacode.amegala.com #Nebraska #Technology #KeynoteSpeaker

10 lessons you need to become an AI/ML engineer: 1. Framing machine learning problems 2. Weak supervision and active learning 3. Processing, training, deploying, inference pipelines 4. Offline evaluation and testing in production 5. Performing error analysis. Where to work next 6. Distributed training. Data and model parallelism 7. Pruning, quantization, and knowledge distillation 8. Serving predictions. Online and batch inference 9. Monitoring models and data distribution shifts 10. Automatic retraining and evaluation of models We cover everything on this list in my program, "Building Machine Learning Systems." And this is just the tip of the iceberg! My program is different from everything you've seen before. It's live. It's pretty hard-core. It's going to challenge you. The program consists of 14 hours of live classes, 8 hours of recordings, 30 assignments, 30 multi-choice questions, and a class project. Multiple companies in the space are hosting exclusive sessions for members (Google, Cleanlab, and Giskard are coming next!) My guarantee is simple: you'll learn more than you've ever done before. • Cohort #9 starts on December 4th • Cohort #10 starts on January 8th • Cohort #11 starts on February 5th Join the community here: ml.school. You will join another 1,000+ engineers who have already gone through the program. To join, you pay once and get lifetime access to every program and session we run. There are no recurrent fees. Ever. Here is the link to join: ml.school. Starting in January, the price will go up. Reply below with any questions.