Piers Stobbs’ Post

Big data and data science are two very closely related terms yet they are very different. Learn about their relationships, key differences, and inter-connectivity here. https://bit.ly/49KI2sx

Big data and data science are two very closely related terms yet they are very different. Learn about their relationships, key differences, and inter-connectivity here. https://bit.ly/49KI2sx

Another successful IT Talks session! 🚀💻 We dove into the world of Data Science with Data Scientist Zeynel Abidin Karadis as our guest speaker. Participants gained insights on becoming a Data Scientist and witnessed a live application showcasing data science in loan decision-making. Big thanks to Mr. Zeynel Abidin Karadis for his valuable insights and engaging presentation! Gratitude to all participants. Check out more details in the link: https://lnkd.in/deCrZRTM #ITTalks #DataScience #MachineLearning

The Data Science Alliance never ceases to amaze me. Their events are top notch. But even more than that, the people are top notch. What have I learned: data science permeates all business and research etc.. that touches our lives. If done right it can extract meaningful insights for business and beyond. Data is scary, for many people. As it has the ability to do great things and not so great things. However with people like The Data Science Alliance users can be more Comfortable knowing their data is being used for good. Join them: https://lnkd.in/d5aSvBU7

Details per article linked in the Comments section below. Written by a Wharton professor of statistics and data science, it really should be one of the leading stories transmitted worldwide currently — the information is that explosive and the explanation that effective…:

Data Science Questions with Answers Series #5 Could you provide examples of Left-skewed and Right-skewed distributions? Additionally, explain the relationship between the mean, median, and mode for each of these distributions.

Your Features Are Important? It Doesn’t Mean They Are Good: “Feature Importance” is not enough. You also need to look at “Error Contribution” if you want to know which features are beneficial for… Continue reading on Towards Data Science »

In data science, when one is obsessed with setting high benchmarks for model performance ends up managing inflated egos & expectations. Not worth it. Focus on real world impact not the benchmarks. ⁉️ Agree ⁉️ #realworldlearning

As we get ready for #DSSNYC! Check out this session: Leveraging Data Science in Credit Analytics with Moody Hadi & Saraansh Arya from last year's event. Dive into a detailed discussion on #MachineLearning and #DataScience in Finance, focusing on #CreditAnalytics. Moody and Saraansh present a robust framework for evaluating these technologies in #creditrisk management, explore innovative methodologies, and look ahead to future research opportunities. https://lnkd.in/gpSZsk-2

"Thrilled to have completed the AlgoTrade Data Analytics Workshop at our college! This hands-on experience has enhanced my skills in algorithmic trading and data analysis, equipping me with valuable insights and techniques for the financial industry. Looking forward to applying what I've learned to real-world challenges! #DataAnalytics #AlgorithmicTrading #ContinuousLearning"