TensorFlow

TensorFlow is useful, although it requires a healthy time commitment to produce accurate models

Kommentare: The benefits I received from this software is more accurate modeling and an interesting insight into what makes one software better than another. TensorFlow did for me what it says it does - produce high quality models, such as neural networks, with a lot of human capital input.

Vorteile:

TensorFlow is fascinating in seeing how it produces results in a reasonable time frame. It is completely flexible compared to its costly competitors. The software connects well with various data sources and in setting up scripts to run automatically.

Nachteile:

TensorFlow takes a lot of time to become an expert in what it is doing. The programming time-commitment might not be worth it unless you plan on customizing your modeling to work with other software.

Relatively Straightforward Deep Learning Framework

Kommentare: Human pattern recognization, image recognization. Habits and trends.

Vorteile:

The 2.0 version is easy to set up and there are a lot of APIs that are integrated for using various programming languages to do the same thing. I personally have been using python with this application and have had very little problems getting going. There are a lot of tutorials on getting started, some good data available for free to assist with the learning process. Everything can be run locally which makes it easy to expand on-site. Cloud options are also affordable.

Nachteile:

The learning curve is a bit steep. This isn't specifically an issue because of TensorFlow itself, the idea of neural networks are not simple. TensorFlow has made improvements on 2.0, that make it easier to use compared to previous versions.

Review of Google Cloud ML Engine

Kommentare: My overall experience with Google Cloud ML platform was very good. I used it's machine learning services to integrate those in my web applications.

Vorteile:

The feature of the Google Cloud ML Engine that I most like is the machine learning features that have been provided by this platform. The ML features of this engine provide SOTA results in every task in machine learning and artificial intelligence. The ML features are very handy and easy to use and integrate in other applications as well. I would recommend everyone to use Google Cloud ML Engine for developing AI systems.

Nachteile:

The pricing, when exceeded the free tier of Google Cloud ML platform, is high. The pricing is high compared to other services like Azure Cloud ML platform.

Deep learning Bestfriend!

Vorteile:

Tensorflow helps me build, train and test models in machine learning and Deep learning. With its commpatibilty to create Deep learning neurons for training purpose and having methods to directly apply it makes tensorflow the best to pursue!!

Nachteile:

So far tensorflow helps even beginners to use it easily with a number of tutorials and documentations making it less likely to have any thing not to like or havee any complaints to users like me.

Feedback

Kommentare: good product

Vorteile:

easy to use. good performance .integration with python is easy

Nachteile:

expensive. AI tools need to be more graphically represented