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31 October 2019
5 min read
If you’ve been keeping informed of what’s happening in the AI and machine learning world, you’ve probably heard a lot of talk about this nebulous thing called the cloud. While the cloud is often used to describe a variety of offerings for decentralized computing, there’s an underlying similarity...
24 October 2019
12 min read
We hear more and more everyday that businesses are sitting on troves of valuable data. It’s compared to precious metals, unrefined oil, or cash in a vault. But those items aren’t valuable simply because they exist. Their value comes from what is created out of them. The same holds true for data....
15 October 2019
5 min read
People often confuse data science and machine learning,  but they are in fact separate entities, despite what the memes say. Let’s make clear what differences there are between data science and machine learning and give some examples of how each is used in business settings. Is data science the same...
14 October 2019
4 min read
Machine learning engineers and data scientists are not the same role, although there is often the misconception that they are synonymous. While there are areas of overlap or reliance on one another, there are very distinct differences between these two roles in computer science.  What is a machine...
8 October 2019
4 min read
Customers have an abundance of options when it comes to products for purchase. This excess of options, however, increases the risk of poor customer retention. Since acquiring new customers costs much more than keeping current customers, a higher retention rate is always better. Customer retention represents...
30 September 2019
2 min read
TensorFlow 2.0 shipped today, 30 September 2019, with new features, such as faster debugging and iteration with Eager Execution, a TensorFlow-enhanced implementation of the Keras API, and simplification and compatibility improvements across its APIs. TensorFlow 2.0 is a major upgrade that should increase...
26 September 2019
6 min read
While consumer-facing applications of machine learning (ML) have gotten a lot of attention (Netflix, Uber, and Amazon) the back office deserves some recognition. Enterprise-level systems that run the business—think finance, robo-advisors, accounting, operations, human resources, and procurement—tend...
19 September 2019
3 min read
Continuous Integration and Continuous Deployment (CI/CD) are key components of any mature software development environment. During CI, newly added code is merged into the codebase, kicking off builds and automated testing. If all tests succeed, then the CD phase begins, deploying the changes automatically...
29 August 2019
5 min read
The financial services industry has often been at the forefront of using new technology to solve business problems. It’s no surprise that many firms in this sector are embracing machine learning, especially now that increased compute power, network connectivity, and cloud infrastructure are cheaper...
23 August 2019
6 min read
In software development, it makes sense to create reusable, portable, self-contained modules that can seamlessly plug into any application. As the old adages insist: rely on modular design, don’t repeat yourself (DRY), and write once, run anywhere. The rise of API-first design, containerization, and...