Sachin Dev’s Post

Nice post. A new worrisome trend in finance is that some academic researchers are advocating for the use of overparameterized/overfit black-box machine learning algorithms to exploit the so-called double-descent phenomenon. While this approach may work well in physical systems, where the underlying laws are relatively constant, it is dangerous in finance. Economic systems are highly dynamic, and the parameters of the data-generating process are unlikely to remain stable, making overparameterized/overfit black-boxes hazardous to investors. To learn more: https://lnkd.in/dS9KMg_3 Aleksander Molak Prof. Alexander Lipton Katie Martin Andrew England Rob Mannix Justina Lee Robin Wigglesworth Mauro Cesa

Building a decision tree classifier to predict whether a customer will purchase a product or service based on their demographic and set from the UCI Machine Learning Repository. #Prodigy#Data science#Task-03

if you want to build your machine learning model. regardless of the task whether it is regression or classification . you can follow these steps. #machinelearning #data #dataanalysis #datascience

Achieving an RMSE of 6.04 in predicting points per game feels like a moderate win, but there’s always room for improvement. Exploring different variables and methods could enhance accuracy—one of the great things about data science is continuous improvement! #PredictiveAccuracy #DataScienceJourney #ModelImprovement #ContinuousLearning

🚀 Exciting News! 🚀 I’ve just published my very first blog on Medium today! 🎉 Dive into the world of Data Science and discover how it’s shaping the future. My post covers the essentials of Data Science, its applications, and its impact on our daily lives. 🔗 Check out the blog here 🔗 I’d love to hear your thoughts and feedback. Let’s explore the transformative power of Data Science together! #DataScience #Medium #BlogPost #Tech #Innovation #Analytics

I realized something: data science isn't just about models and code—it's about persistence. Every error, every retry, is a step closer to insight. Keep going; the breakthroughs are worth it. #Datascience #queryoptimization #machinelearning #dataanalytics

Data Science vs Machine Learning: What's the Difference? Explore the difference between data science and machine learning, providing clarity to those navigating the complex data and technology landscape. Learn more: https://shorturl.at/foI34 #dataScience #machineLearning

Recently came across a very insightful youtube channel which explains many crucial techniques in the world of data!! https://lnkd.in/dUVXRQWa What are your sources for learning new things? #datascience #statistics #machinelearning #dataanalytics

What's one example of how you've used unsupervised learning to uncover hidden patterns in data and what was the outcome? Submit your answer to this question on Featured, and get featured on Data Science Spotlight: https://lnkd.in/gP8KSD_G Deadline: 2024-May-13 #DataScience