Ángel Manuel García Carmona

The development and implementation stage is the most technically creative part of the #DataProductCycle, often associated with algorithms, #machinelearning, and #AI. Read more in our #Substack: https://lnkd.in/ema7kBCu Marco A Morales, PhD #DataScienceShop #datascience #dataengineering #mlengineering

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Read Marcello Politi's article to get a better understanding of Einstein’s notation and einsum multiplication 👉 #AI #MachineLearning #DataScience #DeepLearning

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🚀 Do you want to know the key to impeccable data management? Check out SDG's Tech Station article where #SDGer David Rodríguez Lores reveals how to integrate heterogeneous sources of information for standardized #DataManagement. 🗝️ From #Python to #Snowflake, #AmazonS3 and #MLFlow, we've covered all the bases to make your data analytics project an unprecedented success. Plus, it's adaptable to a variety of programming languages, which means you can reap its benefits no matter your tech landscape. 🌐 Ready to unlock the full potential of your data assets? Don't wait any longer and dive into the article right now ➡️ https://hubs.li/Q02v4znh0 #InsightsBeyondAnalytics #SDGTechStation #GoBeyond

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The second episode of Hillside PatternCast is online! https://lnkd.in/dP4piJWn In this episode, Eduardo Guerra and Hironori Washizaki, talk about important patterns that can be applied when designing a software architecture with components that use Machine Learning.

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🚀 Attention students! 🚀 Are you interested in learning about #LowCoding and how it is revolutionizing #SoftwareDevelopment? Join us for the next event of the Industrial Data Lab, where you will have the opportunity to explore the benefits and functions of #LowCoding and see how it is used in practice at #Bosch. At this event, you will also have the chance to learn about #Bosch as an employer and connect with #Bosch employees over 🍕 pizza and 🍹 drinks. It's the perfect opportunity to network and gain valuable insights into the world of #SoftwareDevelopment. Here's what you can expect: #Bosch as an employer and opportunities for students Overview of #LowCoding platform #OutSystems" and #Knime (Key benefits, platform structure, and core features) Real-world use cases Q&A session Get-together with pizza and drinks 📅 Date, Time: Nov 8, 2024, 11:00-13:00 🏬 Location: Universität Stuttgart, room 0.018 Don't miss out on this unique opportunity to expand your knowledge and connect with industry professionals. Save the date and join us for learning and networking. We can't wait to see you there! ✍ For registration simply contact us! #LowCoding #SoftwareDevelopment #Bosch #Networking #StudentOpportunities #IndustrialDataLab

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On June 20, OpenAlex will host a webinar dedicated to data: ‘Finding, tracking, and analyzing research datasets in OpenAlex’. At the webinar, OpenAlex will cover the work they are doing to index datasets, and Iratxe Puebla from Make Data Count will present on the importance of data citations to understand connections between data and other outputs. Join the webinar on June 20 to hear more about the importance of open infrastructure to evaluate the impact and reach of open data: https://lnkd.in/egTcgu3r #opendata #datametrics

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📈 Dataframe libraries evolving faster than you can keep up? Marco Gorelli's Data Umbrella webinar is your cheat code! Learn Polars expressions and how to build library-agnostic data tools. 👀 Watch now: https://lnkd.in/dpMGfx4a #DataScience #TechTips

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Read this article from the #DenodoCommunity where you will learn the role of the #DenodoPlatform in the typical workflow of #DataScience and #MachineLearning projects. You will also discover how the presence of a #datavirtualization layer in the #dataarchitecture can enhance and speed up the typical tasks of a #DataScientist, such as #dataexploration, #datapreparation and #machinelearning models tuning as well as the tasks of a #DataEngineer, who must address challenges like clean and formalize data preparation code for production

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🚀 Python for Machine Learning: VSC Training The VSC | Vlaams Supercomputer Centrum invites you to explore the fundamentals of machine learning and accelerate your workflows with Python. 📌 Highlights: 🔹 Learn to build and optimize machine learning pipelines using scikit-learn 🔹 Explore key algorithms: Ridge regression, Naive Bayes, k-means, and more 🔹 Dive into deep learning with Keras, including CNNs and RNNs 🔹 Harness GPU acceleration with tools like Numba and Rapids 📅 When? 🗓️ January 13, 2025 | 9:00 a.m.–1:00 p.m. 📍 Where? Online or in-person at ICTS, Heverlee. Whether you’re a VSC user or student, this training is an excellent opportunity to enhance your machine learning expertise. 👉 More info on: https://lnkd.in/eQQSztCd #VSCTraining #MachineLearning #Python #Supercomputing #AI

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Today we invite you to watch a recording of the presentation by invited speaker Jane Dwivedi-Yu from the ML in PL Conference 2023: "Teaching Language models to use tools". https://lnkd.in/dnVHvt8N In this presentation, I will provide an overview of recent advancements in generative modeling using diffusion models. I will begin with a brief introduction, followed by a review of several recent publications that highlight significant progress. These advancements include concepts like classifier guidance, representation learning, selective forgetting, and continual learning within the context of diffusion models. During the presentation, I'll highlight the practical applications where diffusion-based generative models excel and delve into interesting research opportunities that arise from the limitations of these models. Jane Dwivedi-Yu is a researcher at AI at Meta. Her current research focuses on enhancing capabilities of language models along several dimensions, including tool usage, editing, and evaluating representation harms and notions of morality and norms internalized by these models. She is also interested in building large-scale personalized recommender systems by leveraging principles from affective computing, work which was cited among the top 15 AI papers to read in 2022. Before joining Meta, she completed her PhD in Computer Science at University of California, Berkeley and Bachelors at Cornell University.

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💡 Check this #EINST4INE #blog on clustering texts using Latent Dirichlet Allocation (LDA) by #ESR Finn Tryggvason! The post explores how #LDA helps identify hidden themes in documents, making it easier to #analyze and #categorize vast amounts of #information. Read more: https://lnkd.in/dPs39P9M University of Stuttgart #EINST4INE #MSCA #H2020 #ITN #DItigalTransformation #MachineLearning #LDA #DataScience #TextClustering #AI

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