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#machine learning

Developer and tester tips

Chatbot Testing: How to Get it Right in the First Go

Chatbots do more than just messaging. They are rapidly adding value to conversations and have context-driven intelligence that aims to solve customer problems in a convenient matter. This is just the tip of the iceberg. In this article, we will talk about the must-haves in your chatbot testing checklist.

Answering key ML questions

What is Data Annotation and how is it used in Machine Learning?

What is data annotation? And how is data annotation applied in ML? In this article, we are delving deep to answer these key questions. Data annotation is valuable to ML and has contributed immensely to some of the cutting-edge technologies we enjoy today. Data annotators, or the invisible workers in the ML workforce, are needed more now than ever before.

5 main challenges & solutions

What is ML governance?

Why do organizations struggle with ML governance? There are five main challenges that we see our customers face when it’s time to tackle ML governance for their organizations. Learn how organizations can improve and implement an MLOps platform and its impact.

…with Microsoft ML.NET – part 3

Machine Learning 101: Part 3

To conclude what we have covered so far, it’s clear that when building a model, the trainer selection is not the most difficult part. AutoML is able to suggest a list with the best models, grace to the evaluation metrics which accompany every model.

Avoiding DIY disaster

Building Your Own AIOps Platform is a Bad Idea

Why does DIY AIOps fail and what is the root cause? In many cases, all the time and effort put into a do-it-yourself project simply winds up being wasted. This article looks at how to safely encourage AIOps exploration and measure ROI from AIOps without the risk of failure.

… with Microsoft ML.NET – Part 2

Machine Learning 101: Part 2

The purpose of this series of articles is to provide a complete guide (from data to predictions) to machine learning, for .NET developers in a .NET ecosystem, that is now possible using Microsoft ML.NET and Jupyter Notebooks. Even more, you don’t have to be a data scientist to do machine learning.

…with Microsoft ML.NET – Part 1

Machine Learning 101: Part 1

The purpose of this series of articles is to provide a complete guide (from data to predictions) to machine learning, for .NET developers in a .NET ecosystem, and that is possible now using Microsoft ML.NET and Jupyter Notebooks. Even more, you don’t have to be a data scientist to do machine learning.

The fifth form of matter

Introducing software fuzzing – part of AI and ML in DevOps

Justin Reock, Chief Architect for OpenLogic at Perforce Software, describes what is software fuzzing and why it is needed. Justin is the author on a chapter about fuzzing in a new book from Perforce Software: “Accelerating Software Quality: Machine Learning & Artificial Intelligence in the Age of DevOps”.

ML isn't just for Python

Top 5 JavaScript Machine Learning Libraries

As technology advances with the time passing by and so do we – a variety of machine learning frameworks came into limelight such as JavaScript. This article goes over five of the best machine learning libraries for JavaScript and why JS succeeds in the field of ML.

No coding skills necessary

How to Build a Chatbot – All You Need to Know

Michael Larsen, Head of Customer Success & Academy at BotXO.ai, takes us through the essential steps of building a chatbot. A chatbot project should be easy to carry out, easy to maintain and edit, and bring results pretty quickly. It should meet the needs of the business and potential problems to solve, proper flow and content, and integrations.