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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.

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.

How to build an AI Product (8) - Harnessing the Power of Embeddings, Vector Search, and LLMs: A Glimpse into Modern Applications

In the digital age, the continuous evolution of technology propels innovations that were once confined to research labs into everyday applications. Among these advances, the use of embeddings, vector search, and large language models (LLMs) like ChatGPT stands out, ushering in a new era of sophisticated tools that can comprehend,

How to build an AI Product (7) - Build an MVP UI for your backend service

When paired with the robust FastAPI framework, a tool like jQuery can be instrumental in achieving this. FastAPI, known for its high performance and Pythonic ease, serves as an optimal backend choice for modern web applications.

How to build an AI Product (6) - Creating a Docker environment for easy experimentation

Docker has revolutionized the way we build, ship, and run applications. It's an indispensable tool for developers and data scientists, allowing for consistent and reproducible environments. But why Docker? Lets find out.