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In this contributed article, Vara Kumar, co-founder and head of R&D and pre-sales at Whatfix, discusses how in today's competitive landscape, harnessing the full potential of product analytics is pivotal for companies seeking to optimize their internal and external product usage. There are multifaceted benefits of leveraging product analytics, showcasing its ability to provide profound insights into product utilization across an organization.
Introduction Large language models (LLMs) have revolutionized natural language processing (NLP), enabling various applications, from conversational assistants to content generation and analysis. However, working with LLMs can be challenging, requiring developers to navigate complex prompting, data integration, and memory management tasks. This is where Langchain comes into play, a powerful open-source Python framework designed to […] The post A Comprehensive Guide on Langchain appeared fir
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.
Our friends over at Pax8, a leading cloud commerce marketplace, released a new global report in collaboration with Microsoft and Channelnomics on the AI buying trends of Small and Midsize Businesses (SMBs).
Introduction Efficient ML models and frameworks for building or even deploying are the need of the hour after the advent of Machine Learning (ML) and Artificial Intelligence (AI) in various sectors. Although there are several frameworks, PyTorch and TensorFlow emerge as the most famous and commonly used ones. PyTorch and Tensorflow have similar features, integrations, […] The post PyTorch vs TensorFlow: Which is Better for Deep Learning?
Introduction Efficient ML models and frameworks for building or even deploying are the need of the hour after the advent of Machine Learning (ML) and Artificial Intelligence (AI) in various sectors. Although there are several frameworks, PyTorch and TensorFlow emerge as the most famous and commonly used ones. PyTorch and Tensorflow have similar features, integrations, […] The post PyTorch vs TensorFlow: Which is Better for Deep Learning?
Over the last year, we have seen a surge of commercial and open-source foundation models showing strong reasoning abilities on general knowledge tasks.
Lenovo announced the Lenovo ThinkSystem V4 portfolio of Intel-based solutions, powered by Intel® Xeon® 6 processors and designed to make AI accessible while flexibly matching the specific workloads needs of any business. The portfolio includes new AI-enabled solutions that ensure the right mix of AI is available to help customers seamlessly integrate AI into their workflows with new servers that are purpose-built and optimized to maximize performance and efficiency for targeted workloads.
Introduction In today’s information age, data is king. But simply having data is not enough. To truly excel in this data-driven world, we need to be able to transform that data into actionable insights. This is where the DIKW, or Data-Information Knowledge Wisdom Pyramid, comes in. The DIKW Pyramid is a robust framework that helps […] The post The Data-Information-Knowledge-Wisdom Pyramid appeared first on Analytics Vidhya.
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.
Introduction Fine-tuning enables large language models to better align with specific tasks, teach new facts, and incorporate new information. Fine-tuning significantly improves performance compared to prompting, typically surpassing larger models due to its speed and cost-effectiveness. It offers superior task alignment because it undergoes specific training for these tasks.
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
Today, we are excited to announce Databricks LakeFlow, a new solution that contains everything you need to build and operate production data pipelines.
Collaborating on a machine learning project is a bit different from collaborating on a traditional software project. In a machine learning project, engineers are working with data, models, and source code. Additionally, they are also sharing features, model experiment results, and pipelines. You can’t just use any code-sharing platform for a machine learning project; you […] The post 5 Free Platforms to Collaborate on Machine Learning Projects appeared first on MachineLearningMastery
Introduction Many contemporary technologies, especially machine learning, rely heavily on labeled data. In supervised learning, models train using previous input-output pairs to generate predictions or classifications, relying on datasets where each element has an annotation with a label providing background information or indicating expected results.
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.
After completing a course and mastering the essentials of machine learning, it is time to start building machine learning models using real-world datasets. While accessing most real-world datasets can be expensive, platforms like Kaggle offer access to the latest datasets for free on a wide variety of machine learning tasks. In this blog, we will […] The post 5 Free Datasets to Start Your Machine Learning Projects appeared first on MachineLearningMastery.com.
Data privacy has been a long-standing issue that continues to challenge the data industry. Let’s understand how rapid developments in the world of AI have elevated data privacy concerns.
Introduction Stored procedures are a crucial part of SQL databases. They consist of prepared SQL code that you can save and reuse. This feature helps avoid writing the same queries repeatedly. You can call the stored procedure to execute the saved code. Additionally, stored procedures can accept parameters, making them versatile and dynamic. This article […] The post Stored Procedure in SQL appeared first on Analytics Vidhya.
Speaker: Chris Townsend, VP of Product Marketing, Wellspring
Over the past decade, companies have embraced innovation with enthusiasm—Chief Innovation Officers have been hired, and in-house incubators, accelerators, and co-creation labs have been launched. CEOs have spoken with passion about “making everyone an innovator” and the need “to disrupt our own business.” But after years of experimentation, senior leaders are asking: Is this still just an experiment, or are we in it for the long haul?
“FactSet’s mission is to empower clients to make data-driven decisions and supercharge their workflows and productivity. To deliver AI-driven solutions across our entire.
Inpainting and outpainting are popular image editing techniques. You have seen how to perform inpainting and outpainting using the WebUI. You can do the same using code as well. In this post, you will see how you can use the diffusers library from Hugging Face to run Stable Diffusion pipeline to perform inpainting and outpainting. […] The post Inpainting and Outpainting with Diffusers appeared first on MachineLearningMastery.com.
Introduction Imagine a world where your morning alarm adjusts to traffic conditions, your coffee brews to your exact preference before you even get out of bed, and your commute is planned with the perfect balance of speed and scenic detours. This sci-fi dream is becoming a reality thanks to Artificial Intelligence. AI is here to […] The post 25 Ways AI Can Make Your Daily Life Easy appeared first on Analytics Vidhya.
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
Stable Diffusion is trained on LAION-5B, a large-scale dataset comprising billions of general image-text pairs. However, it falls short of comprehending specific subjects and their generation in various contexts (often blurry, obscure, or nonsensical). To address this problem, fine-tuning the model for specific use cases becomes crucial. There are two important fine-tuning techniques for stable […] The post Training Stable Diffusion with Dreambooth appeared first on MachineLearningMastery.
Introduction Many methods have been proven effective in improving model quality, efficiency, and resource consumption in machine learning. The distinction between fine-tuning vs full training vs training from scratch can help you decide which approach is right for your project. Then, we will review them individually and see where and when to use them, using […] The post Fine-Tuning vs Full Training vs Training from Scratch in Machine Learning appeared first on Analytics Vidhya.
In this new webinar, Tamara Fingerlin, Developer Advocate, will walk you through many Airflow best practices and advanced features that can help you make your pipelines more manageable, adaptive, and robust. She'll focus on how to write best-in-class Airflow DAGs using the latest Airflow features like dynamic task mapping and data-driven scheduling!
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