Deep learning holds many mysteries for theory, as we have discussed on this blog. Lately many ML theorists have become interested in the generalization mystery: why do trained deep nets perform well on previously unseen data, even though they have way more free parameters than the number of datapoints (the classic “overfitting” regime)?
http://www.offconvex.org/2017/12/08/generalization1/
http://www.offconvex.org/2017/12/08/generalization1/
Off the convex path
Generalization Theory and Deep Nets, An introduction
Algorithms off the convex path.
An End-to-End Project on Time Series Analysis and Forecasting with Python
https://towardsdatascience.com/an-end-to-end-project-on-time-series-analysis-and-forecasting-with-python-4835e6bf050b
https://towardsdatascience.com/an-end-to-end-project-on-time-series-analysis-and-forecasting-with-python-4835e6bf050b
Medium
An End-to-End Project on Time Series Analysis and Forecasting with Python
Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics…
https://www.smartdatacollective.com/6-questions-to-audit-state-of-companys-analytics-infrastructure/
SmartData Collective
Auditing the State of Your Company's Analytics Infrastructure in 6 Questions
If you're curious about the state of your company's analytics infrastructure, these six questions can help you gain a better understanding of the situation.
https://siliconangle.com/2019/08/20/databricks-intros-automl-tools-building-machine-learning-models/
SiliconANGLE
Databricks intros AutoML tools for building machine learning models
Big-data company Databricks Inc. is hoping to empower so-called citizen data scientists to create their own machine learning models with new "Automated Machine Learning" capabilities in its Unified