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Welcome to insideBIGDATA’s “Heard on the Street” round-up column! In this regular feature, we highlight thought-leadership commentaries from members of the big data ecosystem. Each edition covers the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace.
If you’re reading this article, I assume you already know what machine learning is. But just for a quick refresher, it’s simply making computers smart enough to do jobs that humans used to do, for example, taking attendance using facial recognition. Anyway, moving on to our main discussion, I know there are a lot of […] The post 5 Free Machine Learning Courses from Top Universities appeared first on MachineLearningMastery.com.
Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.
A purpose-built medical LLM developed by Jivi, an Indian startup co-founded by former BharatPe Chief Product Officer Ankur Jain, has claimed the number one slot on the Open Medical LLM Leaderboard.
Introduction In the previous article, we experimented with Cohere’s Command-R model and Rerank model to generate responses and rerank doc sources. We have implemented a simple RAG pipeline using them to generate responses to user’s questions on ingested documents. However, what we have implemented is very simple and unsuitable for the general user, as it […] The post Building RAG Application using Cohere Command-R and Rerank – Part 2 appeared first on Analytics Vidhya.
Introduction In the previous article, we experimented with Cohere’s Command-R model and Rerank model to generate responses and rerank doc sources. We have implemented a simple RAG pipeline using them to generate responses to user’s questions on ingested documents. However, what we have implemented is very simple and unsuitable for the general user, as it […] The post Building RAG Application using Cohere Command-R and Rerank – Part 2 appeared first on Analytics Vidhya.
A loss function in machine learning is a mathematical formula that calculates the difference between the predicted output and the actual output of the model. The loss function is then used to slightly change the model weights and then check whether it has improved the model’s performance. The goal of machine learning algorithms is to […] The post 5 Useful Loss Functions appeared first on MachineLearningMastery.com.
Introduction In SQL and database management, efficiently querying and retrieving data is paramount. Among the various tools and functions available, the CONTAINS function stands out for its capability to perform full-text searches within text columns. Unlike basic string functions, CONTAINS enables complex queries and patterns, making it a powerful asset for developers and database administrators. […] The post What is CONTAINS in SQL?
Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.
Tricentis is a specialist in continuous testing & quality engineering, the company has expanded its developer assistant platform with a new Tricentis Tosca Copilot tool.
We are excited to announce a new data type called variant for semi-structured data. Variant provides an order of magnitude performance improvements compared.
Introduction LlamaIndex is a popular framework for building LLM applications. To build a robust application, we need to know how to count the embedding tokens before making them, ensure there are no duplicates in the vector store, get source data for the generated response, and many other things. This article will review the steps to […] The post How to Build a Resilient Application Using LlamaIndex?
Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage
There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.
Modern data pipeline platform provider Matillion today announced at Snowflake Data Cloud Summit 2024 that it is bringing no-code Generative AI (GenAI) to Snowflake users with new GenAI capabilities and integrations with Snowflake Cortex AI, Snowflake ML Functions, and support for Snowpark Container Services.
Introduction Imagine you’re building a house. You need various tools and materials, right? Python programming works similarly. You’ll often need additional tools beyond the ones with Python by default. These tools come in the form of packages. This is where pip comes in. pip acts as your friendly neighborhood hardware store for Python. It helps […] The post Tutorial for Package Management Using pip Python appeared first on Analytics Vidhya.
Speaker: Andrew Skoog, Founder of MachinistX & President of Hexis Representatives
Manufacturing is evolving, and the right technology can empower—not replace—your workforce. Smart automation and AI-driven software are revolutionizing decision-making, optimizing processes, and improving efficiency. But how do you implement these tools with confidence and ensure they complement human expertise rather than override it? Join industry expert Andrew Skoog as he explores how manufacturers can leverage automation to enhance operations, streamline workflows, and make smarter, data-dri
We don’t need to think about “replacing” coders with AI, we should be thinking about how AI is going to augment, support and extend developers’ capabilities.
Introduction Building and optimizing Retrieval-Augmented Generation (RAG) pipelines has been a rewarding experience. Combining retrieval mechanisms with language models to create contextually aware responses is fascinating. Over the past few months, I’ve fine-tuned my RAG pipeline and learned that effective evaluation and continuous improvement are crucial.
In Airflow, DAGs (your data pipelines) support nearly every use case. As these workflows grow in complexity and scale, efficiently identifying and resolving issues becomes a critical skill for every data engineer. This is a comprehensive guide with best practices and examples to debugging Airflow DAGs. You’ll learn how to: Create a standardized process for debugging to quickly diagnose errors in your DAGs Identify common issues with DAGs, tasks, and connections Distinguish between Airflow-relate
In SAP terms, AI is for business challenges, business problems and business conundrums that need not just solutions, but workable functional resolutions.
Introduction IP address geolocation has become an increasingly useful capability in today’s connected world. This guide will walk through how to track an IP address’s geographic location using Python. We’ll provide code examples that leverage Python libraries to fetch location data like city, region and coordinates for a given IP address.
Documents are the backbone of enterprise operations, but they are also a common source of inefficiency. From buried insights to manual handoffs, document-based workflows can quietly stall decision-making and drain resources. For large, complex organizations, legacy systems and siloed processes create friction that AI is uniquely positioned to resolve.
In this contributed article, Ovais Naseem from Astera, takes a look at how the journey of data modeling tools from basic ER diagrams to sophisticated AI-driven solutions showcases the continuous evolution of technology to meet the growing demands of data management. Understanding how data modeling tools have changed over time gives us important insights into why organizing and analyzing data well is so important.
Introduction Large Language Models are known for their text-generation capabilities. They are trained with millions of tokens during the pre-training period. This will help the large language models understand English text and generate meaningful full tokens during the generation period. One of the other common tasks in Natural Language Processing is the Sequence Classification Task. […] The post How to Finetune Llama 3 for Sequence Classification?
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m
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