Prem Studio vs TensorFlow comparison

"The dataset management feature and the managed finetuning are the most valuable because they save the most time."

"The most valuable feature of TensorFlow is deep learning. It is the best tool for deep learning in the market."

"TensorFlow is a framework that makes it really easy to use for deep learning."

"What made TensorFlow so appealing to us is that you could run it on a cluster computer and on a mobile device."

"It is easy to use and learn."

"TensorFlow improves my organization because our clients get a lot of investment from their investors and we are progressively improving the products. Every six months we release new features."

"Optimization is very good in TensorFlow. There are many opportunities to do hyper-parameter training."

"It is also totally Open-Source and free. Open-source applications are not good usually. but TensorFlow actually changed my view about it and I thought, "Look, Oh my God. This is an open-source application and it's as good as it could be." I learned that TensorFlow, by sharing their own knowledge and their own platform with other developers, it improved the lives of many people around the globe."

"It provides us with 35 features like patch normalization layers, and it is easy to implement using the Kras library when the Kaspersky flow is running behind it."

"The inference should be faster."

"Personally, I find it to be a bit too much AI-oriented."

"It currently offers inbuilt functions, however, having the ability to implement custom libraries would enhance its usefulness for enterprise-level applications."

"The solution is hard to integrate with the GPUs."

"JavaScript is a different thing and all the websites and web apps and all the mobile apps are built-in JavaScript. JavaScript is the core of that. However, TensorFlow is like a machine learning item. What can be improved with TensorFlow is how it can mix in how the JavaScript developers can use TensorFlow."

"TensorFlow deep learning takes a lot of computation power. The more systems you can use, the easier it is. That's a good ability, if you can make a system run immediately at the same time on the same task, it's much faster rather than you having one system running which is slower. Running systems in parallel is a complex situation, but it can improve. There is a lot of work involved."

"TensorFlow Lite only outputs to C."

"It would be nice to have more pre-trained models that we can utilize within layers. I utilize a Mac, and I am unable to utilize AMD GPUs. That's something that I would definitely be like to be able to access within TensorFlow since most of it is with CUDA ML. This only matters for local machines because, in Azure, you can just access any GPU you want from the cloud. It doesn't really matter, but the clients that I work with don't have cloud accounts, or they don't want to utilize that or spend the money. They all see it as too expensive and want to know what they can do on their local machines."

"It would be cool if TensorFlow could make it easier for companies like us to program for running it across different hyperscalers."

"I did not require a license for this solution. It a free open-source solution."

"We are using the free version."

"The solution is free."

"I rate TensorFlow's pricing a five out of ten."

"It is open-source software. You don't have to pay all the big bucks like Azure and Databricks."

"I am using the open-source version of TensorFlow and it is free."

"I think for learners to deploy a project, you can actually use TensorFlow for free. It's just amazing to have an open-source platform like TensorFlow to deploy your own project. Here in Russia no one really cares about licenses, as it is totally open source and free. My clients in the United States were also pleased to learn when they enquired, that licensing is free."

"TensorFlow is free."