Check out this video on how Machine Learning / Artificial Intelligence combined with RPA can help scale automation across different departments in their organization.
Author: Edward Huskin Implementing a neural network from scratch is a deeply valuable exercise, especially for someone just picking up on the fundamentals of machine learning. Once all the concepts have sunk in, writing a library that does something as common as image classification, and OCR is basically attempting to reinvent the wheel. Rather than […]
While healthcare companies don’t seem to be publicizing their efforts into AI for R&D efforts this article details the current AI initiatives at 3 of the largest in the world. Such initiatives include, optimization of numerous processes within their business, claims management, reimbursement, and data management.
Author: Savaram Ravindra Introduction The machine learning systems have been around since the 50s, but there are three major factors at play. They are improved algorithms, more powerful computer hardware, and the enormous increase of data. This is the reason why machine learning has gained a lot of significance than it had in the 50s. […]
See how Mount Sinai is developing large-scale image data in neuropathology for building and evaluating deep learning algorithms to diagnose diseases.
Check out this informative guide on deep learning.
Learn how a software engineer transitioned into machine learning through a data science bootcamp.
Google launches AI Platform to offer developers and data scientists an end-to-end service for building, testing and deploying their own models.
Check out what is in store for data science in 2019. This article isn’t about new fads and concepts, but rather, dark horses – the trends that no one has thought about but will completely disrupt the working IT environment (for both good and bad – depends upon which side of the disruption you are on), in a significant manner.
See how one of the worlds biggest fragrance makers incorporated AI to suggest new formulations for particular markets. The technology gives them a head start on creating something novel, yet took nearly two years — and it required investments that still will take a while to recoup.