Deploying Machine Learning Models in Production_Quiz
개요 Coursera ML Ops Course 4 Quiz 1. Introduction to Model Serving Link: https://www.coursera.org/learn/deploying-machine-learning-models-in-production/home/week/1 2. Introduction to Model
개요 Coursera ML Ops Course 4 Quiz 1. Introduction to Model Serving Link: https://www.coursera.org/learn/deploying-machine-learning-models-in-production/home/week/1 2. Introduction to Model
개요Coursera ML Ops Course 3 Quiz 1. Hyperparameter Tuning and Neural Architecture Search Link: https://www.coursera.org/learn/machine-learning-modeling-pipelines-in-production/home/week/1 2. A
개요Coursera ML Ops Course 2 Quiz 1. Intro to MLEP Link: https://www.coursera.org/learn/machine-learning-data-lifecycle-in-production/home/week/1 2. Data Collection 3. Data Labeling
Course Link Lecture 2 in MLOps Data Label Collecting Data You need to make sure that your data covers the same region of your feature space as the prediction request that you’ll get your trai
개요Coursera ML Ops Course 1 Quiz 1. The Machine Learning Project Lifecycle Link: https://www.coursera.org/learn/introduction-to-machine-learning-in-production/home/week/1 2. Deployment 3. Sel
Course Link Lecture 1 in MLOps Overview the key steps involved in a typical machine learning project. It starts with scoping, where the project goals and variables (X and Y) are defined. Data
개요Coursera Deep Learning Course 5 Quiz 1. Recurrent Neural Networks Link: https://www.coursera.org/learn/nlp-sequence-models/home/module/1 2. Natural Language Processing
Course Link Lecture 5 in Deep Learning RNN there is one-to-many. So, this was a music generation or sequenced generation as example. And then, there’s many-to-one, that would be an example of sen
개요 Coursera Deep Learning Course 4 Quiz 1. The Basics of ConvNets Link: https://www.coursera.org/learn/neural-networks-deep-learning/home/module/1 2.Deep Convolutiona
Course Link Lecture 4 in Deep Learning CNN By convention, in machine learning, we usually do not bother with this flipping operation. Technically this operation is maybe better called cross-corre