Yury Niño Roa’s Post

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The idea that there are different ways to represent predictors in a model, and that some of these representations are better than other, leads to the idea of feature engineering -- the process of creating representations of data that increase the effectiveness of a model. __Page 3, Feature Engineering and Selection, 2019.

Next blog post on @hashnode's engineering blog: How we've built webhooks with Step Functions 🪜

👉 Learn some of the essential aspects of an engineering ecosystem that provide the value promised by Digital Engineering. https://spr.ly/6049WaETv

Measuring Developer Goals Benjamin Ferrari-Church and Carolyn Egelman UNDERSTANDING AND EFFECtively measuring developer goals is critical for enhancing developer experience and productivity. By focusing on durable, consistent, relatable, sensical, and observable goals, we create a more robust view into our developers’ days. #DeveloperProductivity #DevExExperience #EngineeringLeadershipInsights #SoftwareEngineeringBestPractices #MeasuringSuccess #DeveloperGoals #EngineeringProductivityMetrics #SoftwareDevelopmentOptimization #DevOpsEfficiency #DeveloperExperienceMatters https://lnkd.in/gc-B7YHv

Select and customize architectures and hyperparameters using random forest - https://lnkd.in/gfEqfP9i More complex models often can be manually customized to improve how effective they are. Through exercises and explanatory content, we explore how altering the architecture of more complex models can bring about more effective results. Learning objectives In this module, you will: Discover new model types: decision trees and random forests. Learn how model architecture can affect performance. Practice working with hyperparameters to improve training effectiveness. Prerequisites Familiarity with machine learning models https://lnkd.in/gfEqfP9i

Why is not possible to Deserialize without providing output type? Typically if two endpoints are c Check it out: https://lnkd.in/dx27EU7c Join the conversation! #protobufnet

💡 Discover the Capella MBSE tool, which implements the MBSE method 𝗔𝗿𝗰𝗮𝗱𝗶𝗮, emphasizing a clear distinction between needs and solutions. 📚 This tool offers various 𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴 𝗣𝗲𝗿𝘀𝗽𝗲𝗰𝘁𝗶𝘃𝗲𝘀 (Operational, System, Logical, Physical) to assist systems engineers in designing an architecture that meets the requirements of different stakeholders. 👉 Explore how to delve deeper into these perspectives by using the 𝗦𝗲𝗺𝗮𝗻𝘁𝗶𝗰 Browser to navigate traceability links. https://lnkd.in/dSf2X3bB #MBSE #SystemsEngineering #HowTo #Arcadia #syseng

Webinar formal modeling by Professor Holger Hermanns. This is a webinar to shine light on the expertise on software reliability that is already present in the STORM_SAFE consortium. Presentation Professor Holger Hermanns, Saarland University.     #stormsafe #interregnorthsea #stormsurgebarriers #softwarereliability #formalmodeling #criticalinfrastructures #software #europeanunion Universität des Saarlandes

Back to #DSA & #100DaysofCoding Challenge Time Complexity? ❌ Time Complexity is not equal to the Time taken to run a program ✅ Time complexity is defined as the rate at which time taken by program increases with respect to the input size. ----Big O() Notation--- Rules for Calculating Time Complexity 1- Avoid Constants -> like if we have a O(Nx3 + 1) Here 1 is constant value which do not have any effect on the time complexity so we will not consider it. 2- Always compute time complexity considering worst case scenario. ➕ There are 3 cases: Best case, Worst Case and Average Case 3- Avoid Lower Values -- like don't consider exponential values which are very smaller and have no significance. ---Space Complexity--- Memory space a program can take There are two space types involved: 1- Input Space : That you take to store the problem 2- Auxiliary Space: That you take to solve the problem If I am storing N size of array this means that we are using O(N) space complexity. Time and Space Complexity Learnt from: takeUforward