Undoubtedly, your business is run by open source languages; coders of all kinds - from Dev to QA to DevOps - have adopted open source languages. But we’ve also moved from general purpose languages that were easy to adopt to inventing languages that are more suited to niche problem spaces.
Machine Learning (ML) research in the healthcare field has been ongoing for decades, but almost exclusively in the lab rather than in the doctor’s office. The problem of implementing ML in patient-facing settings largely stems from two barriers:
Artificial Intelligence (AI), and more pragmatically, Machine Learning (ML) have been called the new electricity that's powering the Fourth Industrial Revolution (4IR). AI is considered to be the ability for an artificial system to make cognitive decisions without human input, whereas ML is considered to be the ability for a computerized system to improve performance of an automated task over time. While AI is still futuristic, ML has been causing huge disruptions across multiple industries over the past decade. For example:
Technical debt is becoming an increasingly intractable problem for many organizations. Businesses that grew up fast because the only way to survive was to be first to market are now suffering the legacy of unbounded rapid development and workforce churn. There’s a raft of developers and operations folk out there tasked with maintaining a heap of spaghetti code they have little chance of understanding.
When getting started with machine learning (ML) you need data -- and lots of it. Data really forms the foundation of your machine learning strategy and we’ll look at some of the considerations around data in machine learning. In a previous post we built a dog identification microservice in Python. We’ll consider that same use case here when looking at how we need to work with our data.
ActiveState is excited to announce that the Tcl Dev Kit (TDK) is now open source! This critical piece of software enables Tcl developers to create standalone, deployable applications for Windows, MacOS, Linux, Solaris, AIX and HP-UX. The ongoing development of this project has been a joint effort between ActiveState and key members of the Tcl community for many years.
*Note: this post was originally posted on LinkedIn.
We’re starting our own March madness, and it’s all about machine learning (ML). Want to share your ML story? Drop me a Line!
ActiveState has been betting on Python for a while. We’ve been providing companies with Python language-builds since 1999. Since before it became the language of choice for data science projects. So we get why Python would be the means to bridge the worlds of data science and engineering.