Learn the differences between batch and real-time data processing, and explore the decision-making factors for choosing the right approach to optimize data pipelines.
Learn more about Apache Flink, a powerful stream processing tool, for building streaming data pipelines, real-time analytics, and event-driven applications.
This summary of steps to run the PyTorch framework or any AI workload on GPUs highlights the importance of the hardware, driver, software, and frameworks.
Retrieval augmented generation (RAG) needs the right data architecture to scale efficiently. Learn how data streaming helps data and application teams innovate.
Explore the AI/ML capabilities of Snowflake, focusing on leveraging the SNOWFLAKE.ML.ANOMALY_DETECTION function to detect anomalies in superstore sales.
Dive into the concept of semi-supervised learning and explore its principles, applications, and potential to revolutionize how we approach data-hungry ML tasks.
AI and LLMs streamline user story creation, optimize backlog, and predict trends, improving agile product development speed, relevance, and user engagement.
Learn how to create a job in Jenkins, build jobs, and pipeline projects. Explore the Jenkins Freestyle Project, and combine any SCM with any build system.
Explore eBPF, a technology that executes codes in the Linux kernel and is necessary for K8s network observability/monitoring, auditing, and traffic routing.
Building a Meal Planning Bot to Deep Dive into LLMs, Product Development, and Cloud Skills. From Data Generation, to Model Training, to Deployment and App building
Learn how to handle schema versioning and updates in Kafka and other event streaming platforms without using schema registries through custom deserializers.
Explore different approaches to move the pluggable database from source to target database such as plug/unplug, data pump, refreshable clone and DBCA relocate.
Use a combination of real-time speech-to-text, natural language to SQL, and Gen AI, to talk with your data just as you would to a person and in real-time.
CORE
