Juan Antonio Rodríguez Vela

🔔 This paper explores how Cognitive Load Theory (#CLT) can be applied to improve the #explainability, #transparency, #interpretability, and shared interpretability (#ETISI) of #machinelearningmodels. CLT, which analyzes how the complexity of information affects human cognitive effort, is used to understand why certain machine learning models, like Algebraic Machine Learning (AML), may create high cognitive load, limiting their interpretability. Through an analysis of AML and popular explanation techniques such as SHapley Additive exPlanations (SHAP), Local Interpretable Model-Agnostic Explanations (LIME), and Contextual Importance and Utility (CIU), the paper argues that CLT can guide the design of more interpretable machine learning systems. Title "A Cognitive Load Theory (CLT) Analysis of Machine Learning Explainability, Transparency, Interpretability, and Shared Interpretability" By Stephen Fox and Vitor Fortes Rey 🔎 https://lnkd.in/gFVTCAEZ

📢 #fractalfract Special Issue "Analysis and Applications of Fractional Calculus and Mathematical Modelling" is now open for submissions! ⏰ Deadline: 31 March 2025 👉 You can find more information at: https://brnw.ch/21wJ2tg #callforpapers #callforsubmissions #openaccess #fractionalcalculus #fractionalmodels #mathematicalmodelling #fractionaldynamics

【Statistical Analysis of Abilities to Give Consent to Health Data Processing】 Full article: https://lnkd.in/g3Y_Pdus (Authored by Antonella Massari, et al., from University of Bari Aldo Moro (Italy), etc.)   It is important to find a balance between the need to use health data for public health purposes and protecting patient #privacy. This work, based on a pilot survey at the Polyclinic of Bari as part of the "Horizon Europe Seeds" project, aims to promote patients' awareness and trust regarding the processing of their #health_data, ensuring the protection of their rights and privacy, and uses the Personal Health Information Competence Assessment Tool (PHICAT), developed by the medical area of the project, to assess patients' competence to #consent to the processing of health data through a questionnaire. #Cluster_Analysis

📢 Hello LinkedIn community! 🌟💼 🌟 Day 39/50 Days of SQL Challenge 🌟 SQL Bootcamp 2024: Master SQL & PostgreSQL - Hands-On Course https://lnkd.in/gaHnijmg SQL Course 2024: SQL for Data Analysis and Data Science. https://lnkd.in/g45cbiXa SQL Introduction Course 2024: SQL Crash Course. https://lnkd.in/dFyqBHBB Today, let's solve a SQL challenge that involves finding the customer IDs from the `Customer` table who bought all the products in the `Product` table. 🛍️👥 We have two tables: `Customer` and `Product`. The `Customer` table contains information about each customer's purchase, including the customer ID and the product key. The `Product` table contains the product keys for all   Write a solution to report the customer ids from the Customer table that bought all the products in the Product table. Return the result table in any order. The result format is in the following example. Example 1: Input: Customer table: +-------------+-------------+ | customer_id | product_key | +-------------+-------------+ | 1           | 5           | | 2           | 6           | | 3           | 5           | | 3           | 6           | | 1           | 6           | +-------------+-------------+ Product table: +-------------+ | product_key | +-------------+ | 5           | | 6           | +-------------+ Output: +-------------+ | customer_id | +-------------+ | 1           | | 3           | +-------------+ Explanation: The customers who bought all the products (5 and 6) are customers with IDs 1 and 3. Here's the SQL query that will provide the desired results: SELECT customer_id FROM Customer GROUP BY customer_id HAVING COUNT(DISTINCT product_key) = (SELECT COUNT(*) FROM Product); In this query, we use the `GROUP BY` clause to group the records in the `Customer` table by `customer_id`. Then, we use the `HAVING` clause to filter the groups, selecting only those groups where the count of distinct `product_key` values is equal to the total number of products in the `Product` table. The result will be a table with a single column: `customer_id`, representing the customer IDs who bought all the products. Example result: +-------------+ | customer_id | +-------------+ | 1      | | 3      | +-------------+ In this example, customers with IDs 1 and 3 bought all the products (product keys 5 and 6). Feel free to try out this query on your own database or the provided sample data to see the results. Happy coding! 💻🔢 #SQL hashtag #Databases hashtag #DataAnalysis hashtag #LeetCode hashtag #SQL hashtag #DataAnalysis hashtag #DataManipulation hashtag #LinkedInLearning hashtag #ContinuousLearning hashtag #Temotec hashtag #TemotecAcademy hashtag #TamerAhmed hashtag #50DaysOFSQL hashtag #50daysofsqls hashtag #SQLChallenges hashtag #DataAnalysis hashtag #SQLQueries hashtag #DataManipulation hashtag #ProblemSolving hashtag #DataDrivenInsights hashtag

Complete Python Web Scraping : Real Projects & Modern Tools Course Web Scraping with BeautifulSoup, Selenium, Scrapy and Scrapy-Playwright. 4 Project-like Exercises + 4 Real Life Projects In today’s data-driven world, web scraping is a powerful tool that enables you to gather data from websites efficiently. I designed this course to be the most complete web scraping course on Udemy. It is practical and exercise-based, ensuring you learn by doing through exercises and real-life projects. We’ll start with the basics on bookstoscrape and quotestoscrape (which are designed to be scraped) to help you grasp the fundamentals of web scraping. After learning the basics, we’ll dive deep into web scraping on real websites. If you’re new to Python, don’t worry, we’ve got an extra section covering Python fundamentals to get you ready for this course. Get this course now: https://lnkd.in/gkeFGqMa #Python #WebScraping #onlinecourses

Kaggle kaggle.com Kaggle Hi Lava Kafle, You can now find models shared by the Kaggle community! Even better, you can create and share your own models. Check out our full announcement covering how to create your own public model, discover competition models, and what's next. Learn More Earlier this year, we announced that anyone can create models on Kaggle. Early publishers provided feedback, the Kaggle team made improvements, and now we’re ready to welcome your public models! The Kaggle community makes it possible, with public sharing and stress-testing of techniques, code, and resources like models against real-world ML tasks. Now, more than ever, it’s important to make it easier for our community to publicly share and evaluate models, especially LLMs and other generative AI models. If you have any questions or feedback, please let us know in the comments . Meg Risdal, Kaggle Models Kaggle, Inc 1600 Amphitheatre Pkwy Mountain View, CA 94043 This email was sent to [email protected] because you indicated that you'd like to receive news and updates about Kaggle. If you don't want to receive these emails in the future, please unsubscribe here. You can also change your preferences on your account's profile page by logging in at kaggle.com.

CDS-1 2024 Maths Model Question Paper | The NDA-1 2024 mathematics model question paper and solution PDF are attached. Check now: https://lnkd.in/gHekKTT7 #cdsexam #cdsmathsmodelpaper #cdspreviousyearquestions #cds2024exam