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Alfredo Andereleft a comment
Every time that I build the backend of an application I think about how repetitive it is. Spinning up a cloud instances, deploying a web server, serving my code in the correct way, its so tedious and automatable, yet I still have to do it from scratch every time. Not anymore I guess! This product will save me hours every time I make a new product. I can't wait to try it out. Thank you so much...
Napkin BetaBackend in the browser
Alfredo Andereleft a comment
Finally, i've been waiting for a better alternative to good reads for so long. After exploring the product for a while you can be assured that I'm leaving good reads and never looking back.
AfterwordThe simplest personal library for readers
Version data, track models, train on custom clusters - without worrying about setting up infrastructure or cloud compute. Save on cloud costs by only paying for what you need. Run hyperparameter sweeps on multiple nodes with the click of a button.
latch.aiTrain, track and serve machine learning on the cloud.
Alfredo Andereleft a comment
Hey Hunters, happy new year! We realized that low-level machine learning frameworks (i.e. TensorFlow and PyTorch) are great for their flexibility, but they are complicated to learn and require a lot of time and repetitive code. On the other hand, AutoML tools (i.e. Google AutoML, CreateML) are extremely simple to use and abstract away most of the repetitive coding, but they have very little...
FlashMLMachine Learning in Seconds. Dead Simple. PyTorch Flexible.
No-code platform to create and train ML models in minutes:
1) Drag layers, hyper-parameters, and a dataset in the FlashML platform.
2) Download the equivalent PyTorch code with the press of a button.
3) Train your model with a single terminal command.
FlashMLMachine Learning in Seconds. Dead Simple. PyTorch Flexible.
Fast and simple GUI to create PyTorch models.
Drag-and-drop to create your machine learning models.
Download the equivalent PyTorch code.
Train locally with one command line call.
FlashMLDrag & Drop Machine Learning Models w/ PyTorch Flexibility.