MLOps

The field of MLOps has arisen as a way to get ahold of the complexity of industrial uses of artificial intelligence.That effort has so far failed, says Luis Ceze, who is co-founder and CEO of startup OctoML, which develops tools to automate machine learning. "It's still pretty early to turn ML into a common practice,"  Ceze told ZDNet in an interview via Zoom. "That's why I'm a critic of MLOps: we're giving a name for something that's not very well defined, and there's something that's very well defined, called…

Due to the growing importance of MLOPs as a specialization, an aspiring ML engineer has more opportunities than he can typically expect MLOPs has evolved as an independent approach in machine learning, which applies to the entire life cycle from data gathering to model deployment. MLOPs enable the channels of communication between data scientists and operations professionals. A recent study by NewVantage Partners estimated that around 15% of companies have deployed artificial intelligence capabilities into…

Photo by NATHAN MULLET on UnsplashThe Comprehensive Guide to Bash ProgrammingIntroduction:It is inevitable for data scientists, machine learning engineers, or data engineers to learn bash programming. In this article, I will walk through the basics, concepts, and code snippets about bash programming. If you are familiar with python or any other language, then it will be very easy to pick up bash programming. Again the article is more focused on the usage of bash by data scientists, data engineers, and ML engineers. Let us…

How to set up a containerized microservice architecture to run A/B testsPhoto by Jens Lelie on UnsplashMany companies are using data to drive their decisions. The aim is to remove uncertainties, guesswork, and gut feeling. A/B testing is a methodology that can be applied to validate a hypothesis and steer the decisions in the right direction.In this blog post, I want to show how to create a containerized microservice architecture that is easy to deploy, monitor and scale every time we run A/B tests. The focus will be on…

Photo by lucas Favre on UnsplashData engineering, simplifiedIntroduction:LineaPy is a python package used for data science automation. According to the LineaPy documentation:LineaPy is a Python package for capturing, analyzing, and automating data science workflows. At a high level, LineaPy traces the sequence of code execution to form a comprehensive understanding of the code and its context. This understanding allows LineaPy to provide a set of tools that help data scientists bring their work to production more quickly…

Photo by JJ Ying on UnsplashIntroductionOne of the most common challenges in an e-commerce business to build a well-performing product recommender and categorisation model. A product recommender is used to recommend similar products to users so that total time and money spent on platform per user will be increased. There is also a need to have a model to categorise products correctly since there might be some wrongly categorised products in those platforms especially where most of content is generated by users as in case…

MLOPS SPECIALIZATION SERIESFinal insights (with lecture notes) from the Machine Learning Engineering for Production (MLOps) Course by DeepLearning.AI & Andrew NgPhoto by Built Robotics on UnsplashRealizing the potential of machine learning (ML) in the real world goes beyond model training. By leveraging the best practices of MLOps, teams can better operationalize and manage the end-to-end lifecycles of ML models in a sustainable manner.In this final article of the 4-part MLOps Specialization series, I summarize the…