Data Surge的动态

Imagine unlocking the secrets of complex ML models with techniques like SHAP and LIME—crucial tools that illuminate predictions and empower ML professionals to unravel the mysteries within their creations. But don't count out traditional ML! It's the unsung hero, addressing scalability, taming data complexities, and overcoming resource challenges. These algorithms are the backbone of data analysis and predictive modeling, ensuring data scientists wield a powerful arsenal for exploration and discovery. #machinelearning #future #technology #data #datacareer #datascience #PangaeaX #Xmarksthespot

Pipelines and frameworks are tools that allow you to automate and standardize the steps of feature engineering, such as data cleaning, preprocessing, encoding, scaling, selection, and extraction. Pipelining is important because it helps you organize your machine learning workflows and makes your process faster. By linking different steps together, you can save time and effort. Plus, it can help you train your data more effectively. Sir Muhammad Irfan Sir Dr. Sheraz Naseer - (PhD Artificial Intelligence, Data Science). , Sir Muhammad Haris Tariq https://lnkd.in/dhdnfR2E #DataScience #DataAnalysis #featureengineering #pipeline #GoogleAI #Microsoft #chatgpt #IrfanMalik #xevensolutions

??ML In Real World: Beyond Standard Metrics ???I have been thinking about measuring ML model performance in the real world vs. in the lab. As data scientists we are all familiar with common metrics like accuracy/precision/recall/AUC. But in real world to get stakeholders buy-in, you often need to go beyond those metrics. ??In the real world, success is intricately tied to understanding the potential business impacts of a model – the financial costs it incurs and the savings it generates. Moreover, it's about aligning with a company's tech capacity, ensuring that the innovation seamlessly integrates with existing infrastructures. #MachineLearning #DataScience #RealWorldImpact #BusinessMetrics

We just released Metadata-Hub v3.2 with our new AI-powered Metadata Advisor. See how Metadata-Hub is helping research institutes like Max Planck Institute accelerate discoveries, reduce their data preparation time by 95%, and cut storage costs. Metadata-Hub is a data intelligence software platform that streamlines the transformation of unstructured data into a structured, easily searchable format, significantly enhancing its value for analysis and decision-making within organizations. By directly interfacing with storage systems via SMB, NFS, and S3, Metadata-Hub’s unique harvesters can access, open, and interpret any file type, including complex machine-generated data from microscopes, genomic sequencers, telescopes, computer vision systems, etc. By harnessing embedded metadata from a variety of data sources, Metadata-Hub becomes pivotal for fueling advanced analytics, enriching reporting, enhancing AI applications, and streamlining data orchestration. As metadata converges into Metadata-Hub, creating a unified Decentralized Contextual Metadata Platform (DCMP), it can be effortlessly searched, sorted, and provisioned to analytics applications, AI, reporting and other data tools, facilitating a seamless flow of information. #metadata #unstructureddata #datamesh #datafabric #discovery

Drex is now officially live on the Databricks Marketplace! Drex is an AI-powered data extraction tool designed to simplify complex data management processes, particularly for engineering drawings. It helps organizations automate and streamline data extraction, reducing manual effort and ensuring accuracy. By leveraging the power of Databricks, Drex offers enhanced performance, scalability, and seamless integration, unlocking the full potential of your data. We are proud of the team's efforts in bringing this product to market and look forward to seeing the impact Drex will have across various industries. Check it out on the Databricks Marketplace! Click?Here: https://lnkd.in/gV_NZnDr #DatabricksMarketplace #AI #DataExtraction #Databricks #Automation #DataSharing #Engineering Tri Chiem Kent Oczkowski Dean Reynolds Christopher Fletcher Alex Acton Reishin Toolsi Rob Signoretti Jefferson Ye Marco Graziano MANAS GOSWAMI

Kedro, the open-source toolbox for data science, from QuantumBlack, AI by McKinsey recently won an award for its documentation. It was named overall winner of the UK Technical Communication Awards at the TCUK conference in September, signalling its commitment to support users with high-quality content and make it easy-to-use across the ecosystem. In this blog post we explain how the team and Kedro community produces the #documentation using a docs-as-code workflow. #opensource #teamwork #datascience #learning

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?????? ??/???? ???? ?????????????? ???????????????? ???????????? ???????????????????????? ???? ???????? ?????????????????????????? Data preprocessing is a crucial step in the machine learning pipeline. It involves transforming raw data into a clean and usable format, making it suitable for building robust and accurate models. Over the next few days, we will dive deeper into specific preprocessing techniques Here's a comprehensive overview of what data preprocessing steps are ?????????? ???????????????? ?? Follow Punith YC for more !! For Better reach : Akash Kamerkar, Neel Shah, Shakra Shamim, Shashank Singh ????, Munna Das, Mandar Patil, Raghavan P , Gaurav Agrawal,Sneha Vijaykumar ,Shreya Mehta Stay tuned for more insights as we continue our 30-day machine learning journey! #DataScience #MachineLearning #tech #consistency

Attention Data Scientists dive into the future of data science with #3LC, a revolutionary platform that is transforming the #MachineLearning landscape! By delivering granular, real-time insights into model training and data interactions, 3LC is setting a new standard for how data scientists work with their data and models. Business Impact: Boosted Model Performance: Enhanced data quality and insights mean models are not just more accurate, but also more dependable. Increased Efficiency: Our real-time visual tools streamline the machine learning workflow, cutting down on time and operational costs. Informed Decisions: Granular insights into the training process empower teams to make data-driven optimizations to their models. With 3LC, the era of treating machine learning as a "black-box" is over. We're bringing an open, interactive experience to data science, giving professionals unprecedented control and deep insights into their models and the crucial interactions between models and data. By improving dataset quality and training efficiency, 3LC not only enhances the predictive power of models but also provides a competitive edge in the fast-paced, data-driven business world. Apply for Free Prelaunch access at https://3lc.ai/. #DataScience #PyTorch #MachineLearningTools #Innovation #ComputerVision #Classification #TechNews

Imagine exponentially amplifying your data throughput while maintaining immaculate quality. Witness your ML models soar past performance benchmarks, fueled by meticulously labeled datasets ingested at warp speed. Empowered by cutting-edge Active Learning algorithms, ?????????????—Cigniti’s proprietary end-to-end data curation and annotation platform—intelligently prioritizes data points, slashing your image and video data annotation effort by up to 70%. Zastra? has been recognized in“?????? ???????????????? ???????????? ?????????? ??????????????????, ???? ????????” Report by Forrester Watch this explainer video to learn more. #MachineLearning ##DataAnnotation #AIModelTraining