Machine Learning
Anti Money Laundering Algorithms in 2024: Tackling AML with AI
According to the United Nations Office on Drugs and Crime (UNODC), the estimated amount of total money laundered annually around the world is 2-5% of the global GDP ($800 billion – 2 trillion).
What is Few-Shot Learning? Methods & Applications in 2024
Traditionally, developing machine learning systems involves collecting large amounts of data and training ML algorithms on it to produce results. However, Few-shot learning is a hot topic in machine learning where the model makes predictions based on a few training examples. In this article, we’ll explore how few-shot learning works, its applications, and methods.
![45 Statistics, Facts & Forecasts on Machine Learning [2024]](https://research.aimultiple.com/wp-content/uploads/2020/10/Screen-Shot-2023-01-23-at-8.55.33-PM-190x97.png.webp)
45 Statistics, Facts & Forecasts on Machine Learning [2024]
Machine learning is the study of computer algorithms that learn through data. Machine learning is regarded as a subset of artificial intelligence. Surveys and market researches are the best way to understand the overall view of the machine learning market because numbers can reveal metrics from the importance of the market to its challenges.
Decision Intelligence: In-Depth Guide for Businesses in 2024
The unpredictability of the outcomes in today’s decision models often arises from the inability to capture the uncertainty factors linked to these models’ “behavior” in a business context. By introducing machine learning algorithms to decision-making processes, a new field called “decision intelligence” is emerging to create strong decision models in a wide range of processes.
![Machine Learning Accuracy: True-False Positive/Negative [2024]](https://research.aimultiple.com/wp-content/uploads/2019/07/positive-negative-true-false-matrix-190x70.png.webp)
Machine Learning Accuracy: True-False Positive/Negative [2024]
There are various theoretical approaches to measuring accuracy* of competing machine learning models however, in most commercial applications, you simply need to assign a business value to 4 types of results: true positives, true negatives, false positives and false negatives.