Erich Robinson-Tillenburg joins Scott Hanselman to demo and explain health monitoring and configuration analysis for Azure Load Balancer using Azure Monitor for Networks, a central hub that provides access to health and connectivity monitoring for all your network resources.

Time index:

  • [0:00:00]– Overview
  • [0:01:16]– Load Balancer insights
  • [0:04:00]– Visualize functional dependencies
  • [0:06:20]– Exploring the Metrics dashboard
  • [0:10:58]– Flow Distribution Help
  • [0:11:57]– Network Connectivity Monitoring
  • [0:13:18]– Azure Monitor for Networks hub
  • [0:14:12]– Wrap-up

Related links:

Time series are ubiquitous in real-world applications, but often add considerable complications to data science workflows. What’s more, most available machine learning toolboxes (e.g. scikit-learn) are limited to the tabular setting, and cannot easily be applied to time series data.

In this tutorial, you’ll learn how to apply common machine learning techniques to time series and how to extend available toolkits. This is a beginner-friendly tutorial: we assume familiarity with scikit-learn, but no prior experience with time series.

To start, you’ll learn how to distinguish between different kinds of temporal data and associated learning tasks, such as forecasting and time series classification. You’ll then learn how to solve these tasks with machine learning techniques specific to time series data. 

Here’s an interesting use of AI in public safety.

Hongik University’s Professor Lee and his students used AI to develop a new model that can predict the probability of fires. Nothing is more associated with death and destruction than fire. It can produce a primal fear in all of us. So, when a university professor in Seoul, South […]

In this video Krish Naik discusses common myths vs. the realities around the field of Data Science.

Time stamps:

  • 00:37 You need to have a PHD or Masters Degree
  • 01:59 You need a Data Science Certification To Become Data Scientist
  • 03:45 Your Previous Work Experience Is Not Important
  • 05:21 You need to be from Computer Science/ Stats or Programming Background
  • 06:45 Data Science Is All About Model Building
  • 08:20 Kaggle, Hackathon And Real World Projects Are Same
  • 10:03 Most of the time of the project is invested In Model building
  • 11:12 You need to be very good at Coding to get into Data Science
  • 13:04 Freshers can’t get AI jobs
  • 15:45 Final Suggestion From Myside