Hello Twitterverse! π I'm a front-end web developer π» and data science enthusiast π with a love for Rockets π and Non-Fiction π. Looking forward to sharing my insights and thoughts π . Let's connect and explore together!
The best case to move out from this learning hell is by deploying your models, and let users give you feedback about what you have created. πΌ
By doing this you'll play win-win to make you production ready and let you understand the Engineering part of MLE. ππ (4/n)
Students often ask questions like when should they start hitting for the jobs in ML field because it's so simple to train a model and getting high quality predictions π€,
but everyone knows it's not enough. Let me decode the problem here π§ββ (1/n)
To edge out a small increase in performance, learners often resort to techniques that make models too complex to be useful. π
They just focus on getting good matrices on their local machine. π (3/n)
βοΈ 4 ways to Deploy your next GenAI app: ππ€
Indie makers won't tell you this π€«
We are talking about apps that requires GPU.
A thread π§΅ π