For those who haven't found it, yet, OneLook may be useful to you. https://onelook.com/thesaurus. Source: 11 months ago

You might get some mileage out of OneLook Thesaurus or maybe RhymeZone searching by "Related". I prefer them over other dictionary/thesaurus offerings. Source: 12 months ago

OneLook gives a lot of synonyms ranging from close matches to very distantly related words and concepts which I found helps a lot. It also lets you know if certain slang is obsolete or in what specific regions it is used. Source: almost 1 year ago

u/bees-n-sunshine introduced me to Onelook and it's pretty awesome. Source: about 1 year ago

It's worth noting the best thesaurus I've found is onelook. Compare to the solitude results https://onelook.com/thesaurus/?s=solitude. - Source: Hacker News / about 1 year ago

Of course, you can write your own code, in that case, think of it as an interactive matplotlib then! Also, it helps to mention we run a startup Datature, that is a no-code MLOps platform, hence explaining why we are focusing on removing the coding portion of this process :P. Source: almost 3 years ago

A while ago, we announced here that we built Datature and a bunch of users gave feedback and even built MaskRCNN models on our platform! However, we were sending collab updates back and forth - it was a mess. Hence we made Portal for any TensorFlow users to load TF2.0 models (any models off TF2 Model Hub works) and inspect your model visually on your dataset. Source: almost 3 years ago

If you'd like to train a tensorflow object detection model, you can check out https://datature.io - theres about 30 different models you can select from and you can add augmentation to your pipeline. Source: about 3 years ago

If you will be training an object detection model at the end, you can check out https://datature.io - you can annotate your data in browser (no installation) and train an object detection model + deploy when you are done for free! Source: about 3 years ago

Feel free to try it out at https://datature.io - additionally, we are always looking out for feedback and feature requests. We are working more MLOps feature to support teams, so let us know of your thoughts :). Source: about 3 years ago