Adarsh Singh 🎯 (@xdarshsingh) 's Twitter Profile
Adarsh Singh 🎯

@xdarshsingh

🎴Machine Learning @ZSAssociates
• Expert @Kaggle • Building @opensource_ai
• let's join the #AI & #Dev journey ©

ID: 953689478442442752

linkhttps://www.adarshsingh.co.in calendar_today17-01-2018 18:04:25

408 Tweet

102 Followers

92 Following

Adarsh Singh 🎯 (@xdarshsingh) 's Twitter Profile Photo

Just In. Santiago, gonna be publishing a course on MLOps, to do a bit more then just building models. i.e., 👇 • You will know the tools. • You're will be aware of production realities. • You will go the extra mile. Learn more by joining the space. x.com/i/spaces/1eaKb…

Adarsh Singh 🎯 (@xdarshsingh) 's Twitter Profile Photo

In Industry, it's not about just building models, but more about building it's explainability. Anyone can build a model on Kaggle in 5 min, but are you able to explain your assumption or hypothesis? Focus on clarity which inturn will provide the necessary confidence.

Adarsh Singh 🎯 (@xdarshsingh) 's Twitter Profile Photo

People underestimating the power of Excel and suggesting to use Python instead, are the one who never experienced the industrial workspace. Whatever visualization or analysis i can do in python, can be done way better in MS Excel. For data analytics: Excel >>> Python

Adarsh Singh 🎯 (@xdarshsingh) 's Twitter Profile Photo

'Myth vs Truth' of NEEDS in Machine Learning⚡️ ❌Lots of math. ✅Just high school math is sufficient. ❌Lots of data. ✅We've seen record-breaking results with <50 items of data. ❌Lots of expensive computers. ✅You can get what you need for the state of the artwork for free.

Adarsh Singh 🎯 (@xdarshsingh) 's Twitter Profile Photo

You can't go to a Client with a model built with unknown assumptions & 0 explainability. At the same time the Client would never ask you to explain the maths. What you need is clarity in your work i.e., 'Why' & 'How' of Data & Algorithm applied, in terms of business context.

Mark Tenenholtz (@marktenenholtz) 's Twitter Profile Photo

It costs $0.00 to learn machine learning nowadays. You can: • Use Kaggle to scrape your data • Use Kaggle to clean your data • Use Kaggle to build your model • Use Kaggle to rerun your model Kaggle isn't just for competitions. Take full advantage of it.

Adarsh Singh 🎯 (@xdarshsingh) 's Twitter Profile Photo

🎯Studying AI and Machine Learning can raises many interesting questions:⚡️ 1. "Can computers think like humans?"🤔 2. "Can computers be smarter than humans?"✨ 3. "Can computers take over the world?"🤖

Adarsh Singh 🎯 (@xdarshsingh) 's Twitter Profile Photo

Qualities of Good Algorithms❤️ • Input and output should be defined precisely. 📏 • Each step should be clear and unambiguous. 📃 • It should be the most effective approach. 📊 • It shouldn't include computer code. 🧐 🥂

Adarsh Singh 🎯 (@xdarshsingh) 's Twitter Profile Photo

An estimated 87% of models fail to make it into production and team expertise is cited as one of the main reasons for that failure. MLOps is in huge DEMAND !!

Gorm (@metaphorician) 's Twitter Profile Photo

After years of floundering, I think I'm finally getting it: You get energy by spending it. The fuel tank metaphor is completely misleading. The body supplies energy to meet demand. The tank *expands* if you use a lot of fuel. In other words, biology is fundamentally antifragile