Keras: Making Deep Learning More Accessible
People often mistakenly use deep learning and machine learning as synonyms. Actually, it would be more correct to consider deep learning a subset of machine learning and about as similar to traditional machine learning as a calculator is to a computer.
The Key Role Humanities Play in Algorithm Development
As the field of data sciences progresses and algorithms become more refined, topic modelling practices have become more important. This process involves the grouping of objects based on key attributes so that a computer can easily categorize them. This process involves methods of analysis commonly practiced in fields such as literary studies, meaning that specialists in such fields will be essential in further development of related technologies.
The Cloud, Business, and the Future
The cloud is quickly becoming businesses’ preferred method of data management, but it is important to know about where it is going before trusting it fully. In order to best support users, the cloud takes different forms and is continuing to pursue new paths as it evolves. This article by Ronald van Loon is a great resource to learn about the types of cloud and how they might evolve with the aid of artificial intelligence as they are refined.
Be Aware of the Cyber Security Issues Threatening You
As we at Onyx know well, the most important factor in building strong digital infrastructure is maintaining impeccable standards for cyber security. While we do our part in our daily operations, it is essential that regular consumers do theirs. We like the way Security provides a detailed look into some of the most troubling cyber security trends affecting all sectors of our society. Read now.
AI Technology Progresses Too Far for Researchers to Understand
Onyx knows the growing importance of artificial intelligence technology to our society, and a large part of remaining in-the-know is being aware of the ethical dilemmas it presents. We think this article in Wired does a great job explaining the issues facing AI research as it becomes so complex that not even the scientists developing it are able to fully understand what they are creating, and how this may impact the field moving forward. Enjoy!
SSL: Useful Information & Commands
As developers, we know that SSL is quintessential when writing software that communicates securely over networks. Whether it be publishing or consuming REST services or performing enterprise PKI communication in large organizations, knowledge of this topic is important. When I reached the point in my career that I needed to understand SSL, I found it challenging, to put it mildly, to find any sort of consolidated compendium on the subject. More recently developers within Onyx have been coming to me for help on just this topic; hence, this post.
Where Does the Money Come From When User Data is Harvested?
As Antonio García Martínez writes for Wired, user data is often referred to as the “new oil” due to its immense value in the digital world. Understanding how data becomes valuable is key for our operations at Onyx, and for parsing this metaphor. Read more from this interesting article to see why this characterization is not as apt as it may seem and gain a more nuanced understanding of how your information makes money for tech giants.
Data Analytics and the Government: What Could Be Gained?
As data analytics abilities become more refined, parties in the public and private sectors alike have much to gain from using such tools. Recent research carried out by Harvard Kennedy School’s Ash Center for Democratic Governance and Innovation explores the benefits of data analytics implementation and reasons for which the field is swiftly becoming a key area of interest and investment for government leaders. Find out more about recent research into the benefits of data analytics.
Spark Vs. Flink: Comparing the Top Stream Computing Engines
Companies, governmental bureaus, agencies, and organizations rely upon stream computing to process and analyze big data.
Using Blockchain to Ensure Data Integrity for Data Science
Problems with data integrity aren't new. In fact, most sources credit an IBM programmer and instructor from the 1960s with the famous acronym GIGO -- or garbage in, garbage out. Errors or even intentional manipulation of data have always plagued information systems. Even though modern systems may have better features for reducing errors, the very speed data gets generated today multiplies issues. Learn how a relatively new technology, blockchain, can help limit various threats to data integrity in this age of rapid data generation.