Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research and by community contributors.
N/A
Zapier
Score8.9 out of 10
N/A
The Zapier Automation Platform designed to integrate data between web apps. It is scaled for small to mid-sized businesses, with a functional but limited free version of the program.
Caffe is only appropriate for some new beginners who don't want to write any lines of code, just want to use existing models for image recognition, or have some taste of the so-called Deep Learning.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
If you have processes that are now managed and controlled using a spreadsheet, Zapier will give you a lot more control over what is happening and will help you increase productivity by eliminating simple steps such as sending emails and sharing information with your colleagues. It frees time for very transactional activities.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Ease of use - multiple people in the organization can set up and run Zaps per their specific use cases without much training.
Connectivity - Zapier is able to connect to multiple applications we use on a regular basis.
Functionality - Zapier provides embedded functionality within the app itself (email, data conversion), but also appropriate triggers and actions for apps it connects to.
Versatile - Zapier can execute complicated and simple tasks and thus has many use cases.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Caffe's model definition - static configuration files are really painful. Maintaining big configuration files with so many parameters and details of many layers can be a really challenging task.
Besides imagine and vision (CNN), Caffe also gradually adds some other NN architecture support. It doesn't play well in a recurrent domain, so we have to say variety is a problem.
Caffe's deployment for production is not easy. The community support and project development all mean it is almost fading out of the market.
The learning curve is quite steep. Although TensorFlow's is not easy to master either, the reward for Caffe is much less than the TensorFlow can offer.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
The interface is very user-friendly, and there are also many tools to help a brand-new user get started. For example, you can put your Zap idea into the AI bot, and it will basically build a shell of your Zap to get started on. The format for each step within a Zap is also very helpful (set up the connection/app, set up the fields/details, then test).
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Before we purchased Zapier, I contacted support and asked them if Zapier could support my intended workflow (this is actually a selection on their support form - awesome). Within 2 hours, I was contacted by a support team member who seemed sure it would work, but granted me premium access for 2 weeks to try it out for myself. Sure enough, it did! Ever since then, support has replied rapidly to any problems I have experienced and answered my questions within a few sentences.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
TensorFlow is kind of low-level API most suited for those developers who like to control the details, while Keras provides some kind of high-level API for those users who want to boost their project or experiment by reusing most of the existing architecture or models and the accumulated best practice. However, Caffe isn't like either of them so the position for the user is kind of embarrassing.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
We actually utilize both Integromat and Zapier at our company, for all the reasons detailed in this review. Though Zapier is excellent for simple client integrations, we often run into internal use cases that require complexity that Zapier cannot provide. Specifically working with API calls (not just webhooks), complex multi-step integrations with Routing/parsing/etc, and large volume integrations. Integromat is perfect for these use cases, but doesn’t provide the simplicity and account scalability that Zapier offers.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
