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.
Navigating the rapidly evolving AI development landscape poses a distinct challenge, especially when choosing the appropriate tools for developing Large Language Model (LLM) applications. This blog explores Prompt Flow, Semantic Kernel, and LangChain, leading technologies each offering unique features to enhance AI-driven applications.
Read MoreGenerative AI is accelerating a global workforce disruption, the likes of which we have not seen since the Industrial Revolution. But where do you start? How do you ensure you are using AI in legal, responsible, ethical ways? How do you decide you are ready to start employing Generative AI?
Read MoreRetrieval Augmented Generation (RAG) is a framework that provides a more accurate and reliable solution for generating content and interacting with users. RAG addresses the limitations of large language models (LLMs) and helps businesses struggling to generate relevant and accurate content while maintaining credibility and transparency in their interactions with customers.
Read MoreThis 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 MoreExplore the world of AI with Azure OpenAI Service, offering secure access to cutting-edge language models like OpenAI GPT, Codex, and DALL-E within the Azure ecosystem. This article delves into the differences between OpenAI and Azure OpenAI, providing valuable insights to help you choose the ideal solution for your data protection and AI implementation needs.
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 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 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 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 MoreDo you want to get started with computer vision but do not really know where to start? Or would you like to quickly get an idea as to which state-of-the-art (SoTA) computer vision model is best for your task? If you are, then this article will give you a good starting point to jumpstart your computer vision journey.
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 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.
Read MoreWhat do AI, ML and DL mean? How do they relate to each other? This article aims to explain the terms and the differences AI, ML and DL using an incredibly simple example.
Read MoreHow is AI used in finance? What are the top AI use cases that are transforming the finance industry? What benefits does it bring to the financial industry? Read how AI is transforming the finance industry.
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