Author Archives: 365Data Science

How organizations are building resilient coaching programs in a period of rapid transformation For unicorn insurance company Root Insurance, the shift to remote work came quickly. Really quickly. “We decided to make the switch to work from home overnight. We went from everyone in the office to 97% of our company working from home. That’s aContinue reading “The pandemic is widening the agent coaching productivity gap”

Delivering machine learning solutions is so much more than the model. Three key concepts covering version control, testing, and pipelines are the foundation for machine learning operations (MLOps) that help data science teams ship models quicker and with more confidence. Originally from KDnuggets https://ift.tt/34P5tSL source https://365datascience.weebly.com/the-best-data-science-blog-2020/mlops-is-changing-how-machine-learning-models-are-developed

Pomegranate is a delicious fruit. It can also be a super useful Python library for statistical analysis. We will show how in this article. Originally from KDnuggets https://ift.tt/2Ksn4Zo source https://365datascience.weebly.com/the-best-data-science-blog-2020/fast-and-intuitive-statistical-modeling-with-pomegranate

What is Deep Learning and How it Helps to Healthcare Sector? — Cogito Healthcare industry is deeply interested in utilizing the power of artificial intelligence to provide better treatment and patient care at the same time improving their efficiency and lowering the cost of medication and medical facilities. Over the past few years, AI has exploded intoContinue reading “What is Deep Learning and How it Helps to Healthcare Sector?Cogito”

This article presents an overview of some of the most used optimizers while training a neural network. Originally from KDnuggets https://ift.tt/3p48Bl9 source https://365datascience.weebly.com/the-best-data-science-blog-2020/optimization-algorithms-in-neural-networks

Creating an model that works well is only a small aspect of delivering real machine learning solutions. Learn about the motivation behind MLOps, the framework and its components that will help you get your ML model into production, and its relation to DevOps from the world of traditional software development. Originally from KDnuggets https://ift.tt/3mwA7Gm sourceContinue reading “MLOps Why is it required? and What it is?”

Deploying AI ethically and responsibly will involve cross-functional team collaboration, new tools and processes, and proper support from key stakeholders. Originally from KDnuggets https://ift.tt/34rUi1X source https://365datascience.weebly.com/the-best-data-science-blog-2020/navigate-the-road-to-responsible-ai

Also: Know What Employers are Expecting for a Data Scientist Role in 2020; Top Python Libraries for Data Science, Data Visualization & Machine Learning. Originally from KDnuggets https://ift.tt/3r6YI87 source https://365datascience.weebly.com/the-best-data-science-blog-2020/top-2020-stories-24-best-and-free-books-to-understand-machine-learning-if-i-had-to-start-learning-data-science-again-how-would-i-do-it

We’ve gathered best practices for data science and engineering teams to create an efficient framework to monitor ML models. This ebook provides a framework for anyone who has an interest in building, testing, and implementing a robust monitoring strategy in their organization or elsewhere. Originally from KDnuggets https://ift.tt/37tqsfl source https://365datascience.weebly.com/the-best-data-science-blog-2020/ebook-fundamentals-for-efficient-ml-monitoring

In classification problems, the proportion of cases in each class largely determines the base rate of the predictions produced by the model. Therefore if you use sampling techniques that change this proportion, there is a good chance you will want to rescale / calibrate your predictions before using them in the wild. Originally from KDnuggetsContinue reading “Undersampling Will Change the Base Rates of Your Models Predictions”