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Harsh Singhal | DataScienceFM

Harsh Singhal | DataScienceFM

Data Science FM is the #1 Data Science and AI channel online. We help you get started on your Data Science journey with articles and videos that will positively impact your career decisions.

Querying APIs with Python: A Brief Introduction for Aspiring AI Enthusiasts

Whether you're new to programming or just new to Python, this blog post will guide you through the basics needed to query APIs, with a focus on querying language models like OpenAI's ChatGPT.

Harnessing the Power of ChatGPT for Data Science Queries

Welcome back to datascience.fm, where we continuously bring the latest tools and techniques in the realm of data science to your fingertips. Today, we delve into the world of chatbots, specifically focusing on OpenAI's ChatGPT, a variant of the famous GPT-3 model tailored for conversational AI.

Unraveling the Magic of L1 & L2 Regularization

In the world of machine learning, we frequently find ourselves balancing on the tightrope of model complexity. Regularization, particularly L1 and L2, emerges as our safety net, allowing models to learn while being constrained.

Monte Carlo Simulation Across Industries: Real-Life Applications and Case Studies

The Monte Carlo Simulation (MCS) is not merely a fascinating blend of probability theory and computational prowess. Here, we delve into some intriguing real-life examples and case studies.

Bootstrap Statistics Across Industries: Real-Life Examples and Case Studies

Bootstrap statistics, a brainchild of Bradley Efron in the late 1970s, has emerged as a powerful tool for statistical inference, especially when analytical solutions are difficult or infeasible to derive.

Unraveling the Gini Coefficient: A Deep Dive for the Technical Mind

In the world of income inequality, metrics, and indices, there's one term that has certainly captured the limelight – the Gini Coefficient.

Confidence Intervals: A Deep Dive for the Technical Professional

At its core, a Confidence Interval is a range of values we are fairly sure our true value lies in.