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Great product for managing ML
What do you like best about the product?
I like that W&B provides an on-premise solution (in our cloud environment) that allows us to manage our data completely internally. Their python library is easy to use and can integrate quickly with our existing workflows for ML research. Specifically, we're able to automatically collect relevant ML data and display appropriate visualizations to help us find the best models. More generally, W&B lets us better keep track of our models and test various experiments easily.
They have a great reporting feature as well, where we can easily create and share reports relating to our ML experiments. The visualizations also flexible, and we can basically create whatever visuals we want (although with some effort)
I also like that they keep adding more features to help us accelerate and manage all of our ML operations easily. To my knowledge, we haven't made use of all of these features yet (at least Artifacts and Tables), but they will definitely help us with our workflows as we grow and mature our teams.
They have a great reporting feature as well, where we can easily create and share reports relating to our ML experiments. The visualizations also flexible, and we can basically create whatever visuals we want (although with some effort)
I also like that they keep adding more features to help us accelerate and manage all of our ML operations easily. To my knowledge, we haven't made use of all of these features yet (at least Artifacts and Tables), but they will definitely help us with our workflows as we grow and mature our teams.
What do you dislike about the product?
Since we're running on-premise in our cloud, it takes a little effort to maintain the product in our environment.
What problems is the product solving and how is that benefiting you?
Solves where to track machine learning experiments, by providing a single environment for research results to be collected and displayed. This helps our researchers be more productive at doing ML research and finding the best models for our problems.
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Essential tool for ML engineering teams
What do you like best about the product?
Wandb allows my team to collaborate and share information. As soon as we became users of the tool I noticed that we would spend time analyzing the training loss graphs for model runs, and asking each other for help. These runs used to be squirrelled away on people's desktop machines, and were nearly impossible to reconstruct old runs. Now we can look at older runs very easily and our team can collaborate on experiment results. The support from the wandb team has been amazing too.
What do you dislike about the product?
nothing really missing in my opinion. I would like to be able to administer my account a little easier, like seeing how many seats I have left and which users are dormant would allow me to manage my license pool more effectively.
What problems is the product solving and how is that benefiting you?
It gets our engineers collaborating more and speeds up the team, Training these models can be very tricky and have more people analyzing the results from a run really helps us to save time and accelerates our development. Also tracking historical runs is very handy too.
Recommendations to others considering the product:
I highly recommend it.
Recommendation of weights and biases for new machine learning project.
What do you like best about the product?
Support almost all kind of frameworks whether it is pytorch or tensorflow on any other . It integrates very easily with other and collaborative in the real time .
What do you dislike about the product?
Nothing to be disliked about in the application. I can just say i can be more user friendly and interactive. I find some operation that can be very simple but are difficult to use .
What problems is the product solving and how is that benefiting you?
Solving most of my machine learning projects problems as there are very good tools available in the application. I personally use tensorflow framework and it quite easy to use and has many easy tools available.
The most important tool in ML for fast iteration
What do you like best about the product?
W&B is the best platform to support experimental workflows in ML. Rapid turn-around time and extensive experimentation is key to identify what works best, but you also need to keep track and motivate your choices before deploying, especially for safety-critical areas like automomous driving and robotics. W&B enables both: massive experimentation and clear management. Plus having everything in the browser, shareable, and with deep introspection capabilities is a huge productivity boost for any collaborative project. My team and I have been using it since day 1 and we can't live without it!
What do you dislike about the product?
Nothing! The team just keeps adding features and responds really quickly to any of our bug reports.
What problems is the product solving and how is that benefiting you?
Experimentation at scale, hyperparameter search, traceability, research exploration, continuous training and deployment of models.
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