Create Audience Segments Using K-Means Clustering, Churn Prevention with Reinforcement Learning, and AI Foundations
Create Audience Segments Using K-Means Clustering in Python
This mini-tutorial will demonstrate how to get started with K-means clustering in Python using the scikit-learn library and ways to create audience segments that can inform marketing strategies.
State of Machine Learning Survey Results Part One
We recently shared a survey about the current state of machine learning. In the first of two articles, we’d like to share the results, starting with the technical side of things.
5 Must-Know Pillars of a Data Science and AI Foundation
A data science and AI foundation needs to be built up properly before diving in head-first. By knowing these core skills, like math and AI literacy, you’ll start off your career on a high note.
Solve Your MLOps Problems with an Open Source Data Science Stack
These are 10 common problems data scientists face in regard to MLOps alongside some open-source solutions to address them.
Churn Prevention with Reinforcement Learning
Today, churn is the most common data science problem in the world, because every company wants recurring revenue. But how do you go from a churn model to churn prevention? It is much harder than it sounds.
Don’t miss our upcoming Data Primer live virtual training. Join us on March 2nd to learn the foundational skills for success as a data scientist, included in a Mini-Bootcamp pass or as a standalone. Learn more here.
OpenAI CEO on the Potential of AI to Break Capitalism
OpenAI CEO Sam Altman shared his thoughts on how AI could impact capitalism and what the future might look like with AI.
What Does ChatGPT Mean for Business?
In this article, we’ll discuss what ChatGPT is and how businesses can use it to streamline day-to-day tasks.
Tesla’s Automated Driving Documents Have Been Requested by The U.S. Justice Department
The Justice Department recently made a request for information from Tesla regarding its use of artificial intelligence in its self-driving cars.
The Quest to Create AI Therapists
We have chatbots for almost everything, including AI therapists now. How can AI be used to help with therapy on-demand for those who need help?
Startup Behind Stable Diffusion Has Launched a Generative AI for Video
The startup that co-created Stable Diffusion, Runway, has broken new ground in the world of generative AI for video with their latest venture, Gen-1.
7 Ways to Participate at ODSC Europe this June
Between attending in-person or virtually, speaking, volunteering, and more, here are seven ways that you can attend ODSC Europe this June.
Video of the Week: Data-Planning to Implementation
Data planning to implementation is the process of using data to develop and deploy a project or initiative. This involves collecting and analyzing data to identify insights and develop solutions, such as predictive models, visualizations, or machine learning algorithms. The final step is to implement and monitor the solution, refining it over time to ensure it delivers the desired outcomes. In short, data planning to implementation helps organizations make informed decisions and take action based on insights obtained from data.
ODSC volunteers are an integral part of the success of each ODSC conference and a perfect extension of our core team and ambassadors to our community! Learn more about how you can volunteer for either the in-person or virtual team and get a free ticket to the event.
Upcoming Webinars:
How to build stunning Data Science Web applications in Python
Thu, Feb 23, 2023, 12:00 PM — 1:00 PM EST
This webinar presents Taipy, a new low-code Python package that allows you to create complete Data Science applications, including graphical visualization and the management of algorithms, models, and pipelines.
Architectures for Running ML at the Edge
Tue, Feb 28, 2023, 12:00 PM — 1:00 PM EST
In this webinar, we will explore different paradigms for edge deployment of ML models, including federated learning, cloud-edge hybrid architectures, and standalone edge models.
Wed, Mar 8, 2023 12:00 PM — 1:00 PM EST
During the presentation, we will delve into the new tooling additions and will illustrate their functionalities through a hands-on demonstration. In particular, we will show how insights extracted through Responsible AI Dashboard through the identification and diagnosis stage can then be used to ideate and implement different mitigation techniques via the Responsible AI Mitigations library.
