Dive into different approaches to CI/CD at Amazon and Google. The article highlights the unique CI/CD philosophies of these companies, drawing from the author's experience as the Technical Lead for Integration Testing Infrastructure at both.
This article guides you through building a churn model from a business perspective, covering key challenges, the importance of business input in feature creation, and translating business insights into data for a machine learning model.
This article distills critical principles for building practical LLM applications, focusing on a structured approach with a clear SOP, a suitable model, strategic engineering techniques, and relevant contextual data.
What is the future of data scientists? As AI evolves, the role of data scientists is more critical than ever. They focus on enterprise-scale automation and maintaining robust, reliable systems. Learn why precision thinking and the ability to translate business needs into AI solutions will keep data scientists in high demand.
Llama 3.1 is out with eight open-weight models (3 base and five fine-tuned) in three sizes: 8B, 70B, and 405B, all available on Hugging Face. Meta also released Llama Guard 3 and Prompt Guard, models designed to classify LLM inputs and detect prompt injections and jailbreaks.
In this blog, you'll find how to use the Star Schema with Databricks SQL to improve your data warehouse. Learn about boosting performance and scalability with Delta Live Tables for ETL, managed Delta Lake tables, and Liquid Clustering. Discover how the Databricks AI assistant can automate data model creation for seamless AI integration.
Developing and deploying Spark applications was difficult and limited until Spark 3.4. Spark Connect's new architecture allows Spark applications to be written in various languages, including Rust, simplifying development and deployment.
Dive into serverless architecture, AWS Lambda, and the benefits of Lambda Layers for managing dependencies. The tutorial also covers building and managing Lambda Layers using Terraform and GitHub Actions for efficient, automated deployments.
Adel and Jordan explore excel in data science, the impact of GenAI on Excel, Power Query and data transformation, advanced Excel features, Excel for prototyping and generating buy-in, the limitations of Excel and what other tools might emerge in its place, and much more.
Generative AI is rapidly gaining adoption, requiring data platforms to add new features and data teams to take on more responsibilities. In this episode, co-founder of Monte Carlo, Lior Gavish, discusses how data teams are evolving to support AI-powered features and incorporate AI into their work.
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