Vertex AI Reviews & Product Details - Page 47

I love the ability of the GC ML engine to be able to abstract the complexities of ML algos and enable users to learn and use ML using apis. That's simplicity is really awesome! Review collected by and hosted on G2.com.

I think that learning Tensorflow is still quite complex. It might help to have learning aids and prompts which point you in the right direction when Tensorflow does not work as expected. Review collected by and hosted on G2.com.

I like that Google Cloud takes care of ML End to End process flow, I can use buckets to store, tools for monitoring data quality, transform data and spin off TPUs and GPUs as needed for complex algorithms. Review collected by and hosted on G2.com.

Cloud Costs add up; Learning curve for ML/AI scientists to set up Dataflow, IOT, Pubsub etc. Python is not supported everywhere needing Java usage. Review collected by and hosted on G2.com.

I like the measure of capacity you get to store got done with preparing modules. These preparation modules are generally utilized again and again yet separated for each gathering as required. I likewise like the direction given all through the wizards to help guarantee your completed item is great. This program is good to numerous gadgets for me to use at home and at work. The program likewise utilizes my present Google drive in the event that I need to for individual preparing portfolios and modules. Google drive is effortlessly utilized with Google Cloud Machine since it enables me to share and work together with gatherings. I can likewise impart to organization as essential and other area individuals since they additionally utilize the Google stage for proficient utilize. Review collected by and hosted on G2.com.

I think it's on cloud contrasted with other machine learning stages. So once in a while need to experience extra information administration ventures keeping in mind the end goal to put organization information on cloud. Review collected by and hosted on G2.com.

The best of google cloud machine learning is it’s speed. I get minimal latency in my work compared to other data lake option we had in past. Also, I like the way google cloud provides an option to stich my company data with google adwords and double click data. Plus automated machine learning provided by google and tensorflow is additional advantages. Review collected by and hosted on G2.com.

I find google cloud ML a decent product but the only disadvantage I feel is it’s on cloud compared to other machine learning platforms. So sometimes have to go through additional data governance steps in order to put company data on cloud. Review collected by and hosted on G2.com.

i like that i can use ml training and serving as a service. I can programatically set up a series of training jobs Review collected by and hosted on G2.com.

the lack of documentation. you have to guess the concept of operation, constantly go to the help in the command line to explore what is available..... the packaging of your code is annoyingh to do the first two times since you have to guess a lot by following examples. All this could be documented better. Seems like a tool build for cloud/software engineerings trying to do ML than for ML scientist and practitioners. Review collected by and hosted on G2.com.

Using scikit-learn with pandas and numpy is one way to do ML. But to get the efficiency of distributed training, ML Engine is a must have. Review collected by and hosted on G2.com.

Don't have a easy to follow tutorial to learn different aspect of ML Engine. For example, how to use ML Engine to run Hyper-parameter search, how to do data-parallel training or model-parallel training. Review collected by and hosted on G2.com.

Google Cloud ML Engine is an awsome product from the Google Cloud Platform that let's you perform serverless machine learning training of models. It will also automatically optimize your models and last but not least let's you deploy your model in production in minutes. Review collected by and hosted on G2.com.

It still requires some coding ability but I guess that's normal we are still talking about machine learning. Review collected by and hosted on G2.com.

I like the amount of storage you receive to store finished training modules. These training modules are usually used over and over but differentiated for every group as needed. I also like the guidance given throughout the wizards to help ensure your finished product is awesome. This program is compatible to many devices for me to use at home and at work. The program also uses my current Google drive if I want to for personal training portfolios and modules. Google drive is easily used with Google Cloud Machine because it allows me to share and collaborate with groups. I can also share with administration as necessary and other district members because they also use the Google platform for professional use. Review collected by and hosted on G2.com.

I disliked the way that the Google cloud machine learning did not have a common area to find previously created modules to use. This made it necessary to design from scratch. Sometimes time constraints made this difficult and time consuming. Review collected by and hosted on G2.com.

The ease of describing the structure of my neural network and the ease of training it. Review collected by and hosted on G2.com.

I canno think of anything I dislike at the moment. The interface is much cleaner after the introduciton on Keras into this framework. Review collected by and hosted on G2.com.

Easy to run ML Engine jobs via gcloud ml engine commands Review collected by and hosted on G2.com.

ML models are developed using paths to local files. Updating models to use Google Cloud Storage is difficult and there is no documentation on Google Cloud on how to do this. Also updating python scripts to use argparse is trial and error with little documentation. Review collected by and hosted on G2.com.