Predictive Analytics of Donors in Crowd Funding Platforms
Analytics Vidhya
JUNE 30, 2022
The post Predictive Analytics of Donors in Crowd Funding Platforms appeared first on Analytics Vidhya. The project is based on a Kaggle Competition […].
Analytics Vidhya
JUNE 30, 2022
The post Predictive Analytics of Donors in Crowd Funding Platforms appeared first on Analytics Vidhya. The project is based on a Kaggle Competition […].
Aiiot Talk
OCTOBER 17, 2023
Locating and Profiling Potential Donors One potential use for AI in blood banking is to look at available data to find donors. Algorithms can check blood for donor compatibility, reduce overuse, help develop new therapies and locate potential donors. Still, AI is an extremely valuable asset to doctors and nurses.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Unite.AI
OCTOBER 10, 2023
A machine-learning model can use massive data sets to segment donors. Donor Outreach Many people make donations for tax purposes, but even more of them donate because they feel a personal connection to the cause. You can tackle the most common fundraising pain point — donor retention — with AI. While the 2019 rate was 45.4%
ODSC - Open Data Science
FEBRUARY 6, 2023
As data flows from your CRM — including donor profiles, operational data, social media, and more — predictive and prescriptive analytics and benchmarking offer various uses for nonprofits. They can start grouping donors and potential donors based on this data.
ODSC - Open Data Science
NOVEMBER 7, 2023
It can then recommend the most effective ways to connect with donors and keep them interested. Identify Likely Donor Amounts Small-dollar contributions are undoubtedly valuable to nonprofits. Some of the repetition comes from creating donor receipts or thank-you notes.
Towards AI
FEBRUARY 21, 2023
In this approach, the DE/best/1 mutation scheme is employed to create a donor vector vi for each target vector xi in the current generation. The best individual from the population is chosen after boundary checking, and a scaling factor F and a random number r are used to select a layer from xbest or (xr1-xr2) to compute the donor vector vi.
Marktechpost
AUGUST 11, 2023
By analyzing a dataset of 1,66,754 dataset of kidney transplants of deceased donors from (the Scientific Registry of Transplant Recipients)SRTR data using the FIBRES approach, the researchers found the limitations of traditional methods in graft failure risk. Check out the Paper and Reference Article.
Let's personalize your content