Spell Review

The user interface design language for spell was well thought out & easy enough to understand even by someone who has no background in programming or coding at all! It's not very customizable but this can be fixed with some more work from their side as they are open source software. I believe it would have been better if there were options like python3 instead of 2 which might make things easier when using anaconda (which we use). We used NLP techniques mainly text classification tasks such us

It's really easy for my team members who are new in Data Science or ML (Machine Larning) area which helps them learn fast by using this amazing tool with great support from their awesome community! I dislike nothing yet since it has everything what you need as an expert user/developer /data scientist etc.. So if your problem solver needs such type services then i would highly recommend spell because they have all things under one roof so no confusion while searching something here there &…

Easy drag and drop interface for ML algorithms without requiring advanced programming skills. I like how it's easy to use without having to go through training or getting an expert in deep learning models. There was a lot of confusion when using this software because there were too many settings which made some features difficult to find. This can be confusing since you have to understand your own needs before trying out different methods. It wasn't very clear how to make changes so that they…

It has a ton of integrations to other cloud platforms, including AWS and GCP. There is an awesome documentation portal and tutorial library for beginners. However, the biggest drawback of the platform is the pricing. You have to pay for every single server and computer that you use, which can be costly if you're scaling up quickly. It has all the basic functions that you would expect from a machine learning toolkit. Data exploration, feature engineering, modeling, etc. We use Spell extensively