Gavagai vs. Keras

Gavagai is well suited for a B2C business that receives a lot of customer feedback in a form of open-ended text. It makes life easier for the customer experience team to efficiently identify the strengths and areas of improvement for the business. It saves a lot of time and also the hassle of analysing text data manually. It is not just a word cloud tool that shows you the words with the most number of mentions. Gavagai directs you towards actionability.

Incentivized

I would recommend it for use when anyone wants to quickly develop a neural network. Or if a user is solving any machine learning problem that includes deep learning. And this kind of problem will be like image recognition, face recognition, doing some text analysis using deep learning which includes LSTM or some other algorithm.

Incentivized

• Simplifies text data.
• Lets you customise your dashboard.
• Sentiment analysis
• Supports 47+ languages

Incentivized

• Implementing neural networks and deep learning models is easy with this.
• Data processing is easy with Python and Keras. Keras helps a lot and has a good collection of functions to do data processing.
• It has good integration with other devices like Android.

Incentivized

• Auto generated filters based on the data uploaded.
• Adding more Indian regional languages.
• Competitive pricing

Incentivized

• I didn't face any issue so far.
• The only thing, you can't modify everything in this. So it's not recommended for constructing highly optimised algorithms.

The reason for giving this much rating. 1. It makes my job really easy and fast. 2. Strong community support. 3. Overall cost.

Incentivized

Keras have really good support along with the strong community over the internet. So in case you stuck, It won't so hard to get out from it.

I didn't evaluate many options while choosing Gavagai, I had explored a few local vendors whose capabilities were either incomplete or were not up to the mark. Their customer support was also quite poor. Also, the tool was debugged enough which led to frequent crashing. Alchmer although is not a direct competitor to Gavagai, since it's more of a customer feedback tool with additional capabilities of text analytics. I found Alchemer to be extremely expensive. Zonka on the other hand was quite welcoming to feedback from me and promised to develop additional capabilities for my specific requirements although the plan didn't go through due to internal reasons.

Incentivized

As Keras is the high level API, so using Keras, we don't have to be bothered by the low level TensorFlow complexity, and we can reduce a lot coding and testing efforts.

Incentivized

• Helps save man hours.
• Reduces the effort required to analyse big data.
• Helps to act upon areas of improvement faster.
• Indicates the strengths or things that are particularly liked by your customers.

Incentivized

• It helped me in learning the basic concept of deep learning by having hands-on experience.
• It has helped us to implement our NN with very little time.
• It doesn't give you the whole power to customize your neural network. If you want that then you have to shift to TensorFLow

Incentivized