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Use of Federated Machine Learning Effective in Financial Crime Data

Use of Federated Machine Learning Effective in Financial Crime Data Introduction Federated Machine Learning (ML) uses decentralized development processes and model training. In federated ML, a classification or learning algorithm trains on data that node entities store. These node entities are the participating financial institutions in the federal learning process. In such a process, each

Ensemble Learning – Optimal Machine Learning

Introduction Machine Learning Model Management: What It Is: Machine Learning (ML)is on the rise. With that, new problems also keep popping up, and ML developers in collaboration with tech companies keep developing new tools to resolve these problems. MLOps is a group of practices for communication and collaboration between operations professionals and data scientists. Application

Integrating AI and Big Data for Enterprises.

Integrating AI and Big Data for Enterprises Introduction What is Big Data: Big data refers to complex, massive, and high velocity datasets. It is the fuel for the development of Artificial Intelligence (AI). Big data analytics is the use of technologies and processes, including Machine Learning (ML) and to combine and analyze massive datasets with

Advanced Analytics to Address Patient Risk and Deliver Value-Based Care.

Advanced Analytics to Address Patient Risk and Deliver Value-Based Care Introduction Data analytics enables providers to receive insights from various performance management procedures and metrics that comprise the answers to financial viability under pay-for-performance and risk-based contracts. By adopting advanced analytics, health and hospital systems can benefit from all their benefits. Advanced analytics develops a

Machine Learning – The Next Big Thing?

Introduction Do you wonder what powers the highly custom-made recommendations on your mobile from Amazon? Do you wonder how Uber evaluates the arrival times of your booked app cab? All this is thanks to Machine Learning (ML). Let us learn more about ML. Machine learning is a subset of Artificial Intelligence (AI) that enables computer

Making AI More Accessible.

Introduction Artificial Intelligence (AI) has been a topic of interest over the last decade or so. Yet, there are still multiple obstacles present that can hinder businesses from adopting AI. One of the most common obstacles is the cost, as implementing AI technologies and skills can be very expensive. The solution to this problem are

Unsupervised Machine Learning

Unsupervised Machine Learning Introduction In the last decade, we have seen significant progress in Artificial Intelligence (AI) and  Machine Learning with respect to technology with supervised and reinforcement learning – in everything from self-driving cars to photo recognition. Unsupervised learning, also known as unsupervised machine learning, uses Machine Learning Algorithms to cluster and analyze unlabelled

Usage of Data Science in Stock Market

Introduction Data is a cause of concern for all of us. Organizations want to learn how data can help them cut costs and increase profits. The healthcare business also wants to know how data can help them predict illnesses and offer better treatment to its patients. Data science also provides an in-depth understanding of financial

Defining Data Interpretation

Introduction Data interpretation and analysis have now taken center stage with the dawn of the digital age. The sheer volume of data that is being generated is startling. Let us first understand what the term data interpretation means. Data interpretation is reviewing information or data and coming to meaningful conclusions using various analytical approaches. Interpreting