Skip To Main Content
Jeet Singh on Muck Rack

Jeet Singh

As seen in: Medium, The Times of India, TIME, NDTV, Business Standard, BioRxiv, Sify, DEV Community, Scroll.in, Economic and Political Weekly and
Latest Funny SMS and Jokes in Hindi

Get in touch with Jeet

Contact Jeet, search articles and posts on X, monitor coverage, and track replies from one place.

Learn more about Muck Rack

Actions

Share this page

Jeet Singh’s Biography

Read Full Bio →

Read Latest Funny SMS, Santa Banta SMS, School SMS, College SMS, Friendship Jokes, Day Wishes, and Funny Jokes in Hindi at Jokesmasti.

Articles

Sustainable Approaches to Dye Degradation: A Review of Eco-Sustainable Techniques, Recent Strategies, and Emerging Solutions

|
By Praveen Kumar, Kalpana Singh Verified, Jeet Singh
| ascelibrary.org
Get full access to this article View all available purchase options and get full access to this article. Data Availability Statement Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. Acknowledgments The author(s) declared that Generative AI was used in the creation of this manuscript. The authors used ChatGPT (OpenAI) solely for language editing and improving the clarity of this review manuscript.
Open in Who Shared Issue with article?

This was a feature not a bug🐞

|
By Jeet Singh
| DEV Community
A single ESLint error took me on an unexpected journey into the heart of the React Compiler this week. It was a powerful reminder that there's a deep story behind every rule. Here’s what I learned. 👇 The Problem It started with a simple pattern: using an async function inside a useEffect hook. A lint rule flagged my setState call, which I thought was a mistake. Since the state update happened after an await, I was convinced it had to be a false positive.
Open in Who Shared Issue with article?

OpenLearn | Data Preprocessing and Scaling

|
By Jeet Singh
| Medium
In today’s blog, we will learn about data pre-processing, its purpose and its importance in the domain of machine learning. This will create an understanding of Data Preprocessing and scaling in your mind and will answer many of your questions, like- Which tools to use for data scaling? Depending on the data, which tool should we use? Today you’ll learn: -> How to know which encoder to use on a specific feature of the data? -> how and where to use StandardScaler, MinMaxScaler?
Open in Who Shared Issue with article?
See all 795 articles