Data Science & Data Engineering blogs
Thanks for reading. Here you will find a huge range of information in text, audio and video on topics such as Data Science, Data Engineering, Machine Learning Engineering, DataOps and much more. The show notes for “Data Science in Production” are also collated here.
This blog discusses an AI-driven system that uses large language models (LLMs) to empower employees by identifying skill gaps and creating personalized learning paths. The system acts as a personal career coach, providing tailored feedback and growth opportunities.
Read MoreFabric wouldn’t be an end-to-end data analytics platform without data science, so in this blog we will explore that data science and machine learning capabilities of Microsoft Fabric and assess where the platform fits in the completive data science landscape.
Read MoreAre you struggling to deploy your machine learning models in the cloud? With so many options available, it can be overwhelming to know where to start. In this blog, we'll explore how Azure's Managed Endpoints can simplify the deployment process and provide a user-friendly interface for deploying and managing machine learning models.
Read MoreStruggling to choose a machine learning platform for building and deploying models? Check out our blog on 10 reasons why Azure Databricks for machine learning is a great choice.
Read MoreWe are thrilled to announce our partnership with Dataiku, the leading platform for data science and machine learning. Dataiku's Everyday AI platform offers powerful tools, intuitive capabilities and allows for collaboration between code-first data scientists and non-coding colleagues. The platform can also be integrated with Microsoft Azure and Databricks, driving innovation in the field of data science and ML. With Dataiku, we are able to offer our customers access to the latest in data science and ML tools, enabling advanced and sophisticated solutions to meet their business needs.
Read MoreKnowing your customers inside out is key for any business. But getting a full understanding of what they want and need can be challenging. That's where machine learning (ML) comes in. By using ML-driven customer 360 views, you can get a better understanding of your customer's buying habits, preferences, and needs. This can then be used to make your marketing more personal, and improve the customer experience while increasing sales through cross-selling and upselling.
Read MoreAre you having trouble getting value out of your company's unstructured data? Optical character recognition (OCR) could be the answer. OCR technology allows businesses to turn unstructured documents and images into structured data, enabling them to make informed decisions. This technology can be used in various industries, including healthcare, finance, legal, and retail, to streamline processes and gain valuable insights. Discover how OCR can transform your business now.
Read MoreCustomer retention is important for the success of a business and can be improved through the use of machine learning models to predict churn. FLAML is a tool that can help businesses easily build these models. By retaining customers and preventing them from switching to competitors, businesses can increase revenue, save costs, and improve brand loyalty.
Read MoreThe future of data is AI. However, most companies still face a challenge when it comes to productionising machine learning models. Last week, at the AI and Data summit, Databricks unveiled MLFlow 2.0, a new feature coming soon that features MLflow Pipelines to accelerate the deployment of machine learning models.
Read MoreWondering how to create the best marketing strategy to reach out to different customer groups? Do you know which groups of customers are most likely to buy your product? Clustering your customers into segments based on profiles, behaviours and buying patterns is the answer. This article provides a great way to jump-start your clustering project using pre-built code designed by Databricks.
Read MoreDo you know what the 10 most commonly useful clustering algorithms are? If you wondering what they are, then this article is for you.
Read MoreThis article uses an easy and simple example to explain what clustering is and how it is being used in business to solve problems.
Read MoreAutomated Machine Learning, or AutoML, has gained a lot of popularity. Recently, cloud providers have introduced the capability of AutoML for computer vision tasks. In this article, we explore the concept of AutoML for vision and see how computer vision is revolutionising many industries.
Read More10 ways AI & Machine learning can be used to drive revenue in Insurance & Brokers.
Read MoreDo you know exactly how many of your customers are leaving? Do you know why your customers are leaving? Are you able to predict which customers will leave the service? This article will show you how to predict churn using Azure Synapse Analytics and Azure Machine Learning.
Read MoreFeature stores are rapidly gaining popularity in the machine learning environment. Find out what feature stores are all about and the benefits they offer when implemented in a machine learning pipeline.
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