Top Rated TFLearn Alternatives
TFlearn is fully transparent when compared to TensorFlow. All functions are built over tensors and can be used independently of TFLearn.It also supports most of deep learning models. Review collected by and hosted on G2.com.
I dislike the requirement to update TensorFlow to avoid incompatibility issues and the fact that not all deep learning models are supported by TFLearn. Review collected by and hosted on G2.com.
Video Reviews
19 out of 20 Total Reviews for TFLearn
Overall Review Sentiment for TFLearn
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I am working on an application with deals with customer interaction using chatbox. TFLearn helps me to create the request and responses for the client. Review collected by and hosted on G2.com.
The only trouble I had was to learn this new framework as this was my first experience with this kind of technology. It took me sometime to understand as not much content available on Review collected by and hosted on G2.com.
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We can use Tensorflow to build up neural networks easily. yet, TFlearn has made this task even easier with its built-in functions and this leaves me to do less amount of coding. While Tensorflow needs around 12 lines of coding to build a fully connected neural networks, TFLearn builds the same neural network with only five lines od coding. Further, TFLearn provides very useful and descriptive visualization on the built deep NN. It supports not only deep NNs but also other NN architectures such as CNN, LSTM etc. as well. Review collected by and hosted on G2.com.
One of the drawbacks of TFLearn is, it is possible to have issues in executing your algorithms after updating the API due to depreciation of certain functions. Yet, this also not be the case sometime. Yet, it is better if the developers of TFLearn can take care of this issue as well. Review collected by and hosted on G2.com.
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The best thing related to TFLearn is it have inbuilt functions for all the machine learning functions and equations in a single line of code most of the time. Therefore I feel like it is the best rapid prototyping tool that can be used to develop fast deep learning models. The next best thing that I love is TFlearn has not of tutorials and backup support. The matrix operations are handled by the Tensorflow developed by Google. The TFLearn runs on top of Tensorflow. The next best thing is that it supports normal CPU operation and also the GPU operation. It runs very fast on CUDA cored GPU. Easy to test models on different devices. Review collected by and hosted on G2.com.
It is a bigger library. Updates are done to the library very frequently. Once I had an issue with the version of the library. After installing the previous version of the TFLearn the problem was solved. Other than that problem no other problems were occurred as for my experience. Review collected by and hosted on G2.com.
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I work in the law IT field and this framework has helped us to create good network of vast data available through deep learning. Review collected by and hosted on G2.com.
It was hard to explain this to business and other stockholder of the team. It's not very big disadvantage as they are not aware with technologies much but it will be great to have some documents for know technology people. Review collected by and hosted on G2.com.
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Graph visualization, easy to learn and use, developing NNs very fast and super efficient, you can cut off your code at least in half. It support CNN and LSTM as well also supports for multiple DNN. It can beat sklearn's API . Review collected by and hosted on G2.com.
Poor community, if you look for a question, its not easy to find the answer in forums. I recommend create a video tutorial for this API and put it in somewhere like Udemy, so People can get familiar easily. Review collected by and hosted on G2.com.
I had a great experience with the TFLearn platform. The best part is from careful attention to the design and details of the professional content. I would definitely use this again and highly recommend this to my co-workers and friends! Review collected by and hosted on G2.com.
Not much to write on this. I am happy that I don't have any issues with the platform. Review collected by and hosted on G2.com.
TFLearn is a very useful tool to have in your ML toolkit if you are dealing with neural networks more often. it is quite easy to understand and use . provides all solutions. Review collected by and hosted on G2.com.
don't fell it has any issue till now. all functions are working quite well. interface are quite good. i just advice to make it's GUI more user friendly Review collected by and hosted on G2.com.
Fast prototype, it’s easy to prototype the idea fast Review collected by and hosted on G2.com.
No so friendly as Keras,
Looking for a feature what keras offers
I was looking for LSTM3D but didn’t find in TFlearn in keas I found a thread where it’s official coding I don’t started
Make library rich Review collected by and hosted on G2.com.
The best thing about TFLearn is it's seamless experience with graph visualizations showing all the details about weights, gradients and activations. Review collected by and hosted on G2.com.
It's been seamless so far and there is nothing I dislike. Review collected by and hosted on G2.com.