Colaboratory for G Suite Reviews & Product Details

The service provided is just a steal price and rates are also flat. You get up to 50+gb ram is high ram runtime and p100 always and v100 too sometimes which is more than twice faster than p100.

It also provides background execution so that after the training has started the tab can be closed and later on when opened the code will still be running.

You can also run GPU sessions easily in parallel without any problems.

you get more than 100 GB of available disk space to save the results or download the data to carry out your experiments. Review collected by and hosted on G2.com.

The only thing I didn't like is the fact that sometimes you can't get v100 for a whole month but considering the price, even a 20-hour use on p100 would be costing more on other cloud services so you still get value for money.

Also, the connection only lasts for a straight 24 hours max and this figure can vary in the range of 18-24 hours depending on the particular runtime selected.

e.g. a high ram runtime with you will most likely last shorter as it is the most resource-consuming of all than a normal runtime on CPU. Review collected by and hosted on G2.com.

The notebook provides free memory and disk space for community use. It has multiple integrated features and libraries for common use and it's pretty fast and efficient to work with. It also provides integration with G-drive and other Google services. Review collected by and hosted on G2.com.

Not much to be honest, it saves my life. But sometimes the servers are busy when many developers are using it for the same time and that causes a nuisance but for a free service no one can complain. Review collected by and hosted on G2.com.

Google Colab interface is very identical to Jupyter Notebook; that's what makes it easy to work in it, plus it gives the following things for free:

- 13GB(approx.) of RAM

- A choice between CPU and GPU

- A large disk

- Can mount with google drive to save models Review collected by and hosted on G2.com.

It is perfect for people working on low-end devices and ideal for those who don't want to cook their system training deep learning models. A few things which annoy me are

- it disconnects very soon for inactivity, which should be increased.

- if you forgot to save the model in google drive you might loose all the data which could be problematic assuming how long does it took to train it. Review collected by and hosted on G2.com.

It's one of the most convenient notebooks for writing codes, especially related to Data Science. It has clear cells, good, distinguishable, and colorful fonts, and it can be used online, so there's no need to download it. We can write texts and add pictures for explanation and documentation purposes as well. Quite easy to use. The best part is it comes with GPU and TPU for faster computing. It can also directly connect to GitHub to access code files/datasets. Also, a good part is most of the top libraries used in ML tasks are already present in it. Review collected by and hosted on G2.com.

Its premium/pro version is a little on the costlier side. Also, the space provided to us to run/process our models can be increased for the free version, sometimes MemoryError comes. Otherwise, highly recommended. Review collected by and hosted on G2.com.

Colaboratory Is a revolutionary tool. It is easy to install and a great tool to start coding Python and experimenting. It is extremely fast and has instant saving options to secure your versions control. Great for prototyping and analytics work. Review collected by and hosted on G2.com.

Colab is an excellent working and research tool. It is a pleasure for me to give a review. Review collected by and hosted on G2.com.

The best thing about Google Colaboratory are:

> Easy to use.

> Free to use given CPU and some GPU.

> Works fully in Cloud.

> Easy connect to drive and access files.

> The CPU is really fast and helps a lot in training models. Review collected by and hosted on G2.com.

There are some small things that I dislike about it:

> Some libraries must be installed before running it.

> Takes a lot of time while loading data from the drive.

> No options to extract the notebook in HTML and other forms only supports .ipynb and .py file for export. Review collected by and hosted on G2.com.

The ability to mount Google Drive to the notebook and pull data directly from there. Also supports a good flow between other Google products (such as BigQuery). For BigQuery, it allows running queries directly in the notebook and piping into the pandas data frame. Helps with managing the packages and dependencies. Review collected by and hosted on G2.com.

Some modules that are not explicitly built into Colab can cause issues. Processing times do not scale well on large datasets. Review collected by and hosted on G2.com.

Run experiments free of cost. Prototype and learn. Review collected by and hosted on G2.com.

Low gpu memory in free tier. Strict limit for inactivity. Review collected by and hosted on G2.com.

Easy handle and free access to CPU and GPU both Review collected by and hosted on G2.com.

Sometimes it automatically disconnected and we lose scripts run Review collected by and hosted on G2.com.

1. for every error it will auto-generate stack overflow URL to solve the issue. 2.It is simple to use and is hassle-free to install different environments in the system. It is easy to save the code as it directly links up to the drive. Review collected by and hosted on G2.com.

1. error output console is not legible enough to understand the errors easily. 2. I wish there was a numbering system even if the code is entered in a new section each time. It is difficult to follow the numbers mentioned in error. Review collected by and hosted on G2.com.