ML ReferencesMay 21, 2021 One-minute readmachine-learning • mlopsML Foundations https://github.com/chiphuyen/machine-learning-systems-designhttps://jovian.ai/learn/data-structures-and-algorithms-in-python/lesson/lesson-1-binary-search-linked-lists-and-complexityhttps://madewithml.com/https://sebastianraschka.com/resources/ml-lectures-1.html#l11-model-evaluation-part-4----statistical-tests-and-algorithm-selectionhttps://whimsical.com/CA7f3ykvXpnJ9Az32vYXvahttps://www.coursera.org/learn/machine-learninghttps://ds-path.netlify.app/sections/ml-pathDeep Learning https://fall2019.fullstackdeeplearning.com/https://d2l.ai/https://www.coursera.org/specializations/deep-learninghttps://www.deeplearningbook.org/https://course.fast.ai/NLP https://lena-voita.github.io/nlp_course.htmlhttps://www.fast.ai/2019/07/08/fastai-nlp/http://web.stanford.edu/class/cs224n/index.html#courseworkAI https://www.deeplearningbook.org/MLOps https://docs.cloudera.com/machine-learning/1.1/product/topics/ml-challenges-in-prod.htmlhttps://databricks.com/blog/2019/09/18/productionizing-machine-learning-from-deployment-to-drift-detection.htmlhttps://www.fullstackpython.com/MLOPs tutorial by DVC and CMLhttps://mlflow.org/https://www.kubeflow.org/ebook: Building ML powered applicationsebook: introducing MLOpsebook: Machine Learning Design Patternsebook: Building Machine Learning Pipelines: Automating Model Life Cycles with TensorFlowhttps://neptune.ai/blog/deep-dive-into-error-analysis-and-model-debugging-in-machine-learning-and-deep-learninghttps://neptune.ai/blog/concept-drift-best-practiceshttps://cloud.google.com/solutions/machine-learning/mlops-continuous-delivery-and-automation-pipelines-in-machine-learning?hl=es-419https://neptune.ai/blog/best-ml-experiment-tracking-toolshttps://university.datarobot.com/mlops-starterhttps://ml-ops.org/https://en.wikipedia.org/wiki/MLOpsMachine Learning Engineering for Production (MLOps)MLOps Tooling Landscape v2 - Chip Huyen