# TFLearn Reviews **Vendor:** TFLearn **Category:** [Artificial Neural Network Software](https://www.g2.com/categories/artificial-neural-network) **Average Rating:** 4.0/5.0 **Total Reviews:** 20 ## About TFLearn TFlearn is a modular and transparent deep learning library built on top of Tensorflow that provide a higher-level API to TensorFlow in order to facilitate and speed-up experimentations, while remaining fully transparent and compatible with it. ## TFLearn Reviews ### 1. Easy to learn framework **Rating:** 4.0/5.0 stars **Reviewed by:** Ashutosh S. | Associate Director, Small-Business (50 or fewer emp.) **Reviewed Date:** August 30, 2019 **What do you like best about TFLearn?** I like TfLearn because of it very easy to learn still provides all complex functions. I have observed the it perform better in comparison to similar frameworks available in the market. **What do you dislike about TFLearn?** When I started working with TfLearn, I had to learn Python also. I am used to working with Java. It will be great if we can have some API to work with Java also. It will allow so many people to connect with TfLearn. **Recommendations to others considering TFLearn:** More language support will help. **What problems is TFLearn solving and how is that benefiting you?** I am trying to create one projection application, which takes data from the last few years and is updated on a daily basis so the projections need to be updated on a real-time basis. TFLearn helps me calculate those projections. ### 2. Best framework for NLP **Rating:** 4.0/5.0 stars **Reviewed by:** Shipra J. | Consultant Level 6, Investment Banking, Small-Business (50 or fewer emp.) **Reviewed Date:** September 04, 2019 **What do you like best about TFLearn?** 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. **What do you dislike about TFLearn?** 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 **Recommendations to others considering TFLearn:** We need some more tutorials for bignners and video tutorials will be better. **What problems is TFLearn solving and how is that benefiting you?** As I explained we are creating an application which has a chatbox component. TFLearn helps us to provide NLP module in that. This gives us and advantage to provide better value to users of application. ### 3. An easy-to-use and efficient API for building deep NNs very fast **Rating:** 5.0/5.0 stars **Reviewed by:** Chathuri J. | University Undergaduate, Small-Business (50 or fewer emp.) **Reviewed Date:** February 26, 2019 **What do you like best about TFLearn?** 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. **What do you dislike about TFLearn?** 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. **Recommendations to others considering TFLearn:** TFLearn is a very useful tool to have in your Machine Learning toolkit if you are dealing with neural networks more often. The TFlearn tutorial is also available which will give a thorough guide in starting to use the API. TFlearn has the ability to build up different types of deep learning models in a very short time with less effort. Therefore, TFLearn can be highly recommended to any ML practitioner. **What problems is TFLearn solving and how is that benefiting you?** Currently I am working on a project which is involved with machine vision. There, I had to implement a Convolution Neural network to extract some information from image data. In completing this task, TFLearn was a very useful tool as it reduces the whole coding amount and its tutorials were also very helpful to me. ### 4. rapid prototyping tool for deep learning models **Rating:** 5.0/5.0 stars **Reviewed by:** Aruna J. | Research Assistant, Small-Business (50 or fewer emp.) **Reviewed Date:** February 24, 2019 **What do you like best about TFLearn?** 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. **What do you dislike about TFLearn?** 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. **Recommendations to others considering TFLearn:** TFLearn is the best prototyping tool for featuring more high-level function for Tensorflow. Most of the new Machine learning and deep learning products are developed on top of Tensorflow library. Therefore if you do experiments with deep learning and ai models TFLearns speed up them. Just you can implement models with less number of code lines. **What problems is TFLearn solving and how is that benefiting you?** Developing deep learning models, rapid prototyping deep learning models, Testing different activation functions with the output behaviour. ### 5. Super easy to implement **Rating:** 5.0/5.0 stars **Reviewed by:** Shakha J. | Associate, Small-Business (50 or fewer emp.) **Reviewed Date:** September 07, 2019 **What do you like best about TFLearn?** I work in the law IT field and this framework has helped us to create good network of vast data available through deep learning. **What do you dislike about TFLearn?** 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. **What problems is TFLearn solving and how is that benefiting you?** We have a Artificial inteligance based database to search for different cases. This framework help us through deep learning to solve this problem. ### 6. Get deep in an easy way. **Rating:** 4.0/5.0 stars **Reviewed by:** Mahmoud M. | Software Developer, Computer Software, Enterprise (> 1000 emp.) **Reviewed Date:** August 12, 2019 **What do you like best about TFLearn?** 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 . **What do you dislike about TFLearn?** 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. **What problems is TFLearn solving and how is that benefiting you?** Multiple DNN implementation, learn tensorflow. Since is friendly use API for someone beginner like me was super helpful. ### 7. TFLearn makes it easy to build TF Models **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** November 18, 2019 **What do you like best about TFLearn?** 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. **What do you dislike about TFLearn?** I dislike the requirement to update TensorFlow to avoid incompatibility issues and the fact that not all deep learning models are supported by TFLearn. **Recommendations to others considering TFLearn:** Take the time to compare TFLearn to Keras and you will notice how cleaner TFLearn syntax is. **What problems is TFLearn solving and how is that benefiting you?** I have used TFLearn for face recognition, image classification, and time series modeling (CNN & LSTM). ### 8. Temple of Learning **Rating:** 4.5/5.0 stars **Reviewed by:** Srinathji K. | Big Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** September 04, 2019 **What do you like best about TFLearn?** 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! **What do you dislike about TFLearn?** Not much to write on this. I am happy that I don't have any issues with the platform. **What problems is TFLearn solving and how is that benefiting you?** It really helps to solve big problems especially in our retail domain/sectors ### 9. One of the best prototyping tools for featuring more high-level functions for TensorFlow. **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) **Reviewed Date:** August 29, 2019 **What do you like best about TFLearn?** 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. **What do you dislike about TFLearn?** I don't feel it has any issues until now. All functions are working quite well. The interface is quite good. I just advise to make its GUI more user-friendly. **Recommendations to others considering TFLearn:** The interface is good. Try to make its GUI more user-friendly. **What problems is TFLearn solving and how is that benefiting you?** It is quite easy to understand and use. It provides all solutions. ### 10. 4 years of experience in machine learning **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Hospital & Health Care | Enterprise (> 1000 emp.) **Reviewed Date:** September 02, 2019 **What do you like best about TFLearn?** Fast prototype, it’s easy to prototype the idea fast **What do you dislike about TFLearn?** 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 **Recommendations to others considering TFLearn:** Keep library updated with recent research and advancement. **What problems is TFLearn solving and how is that benefiting you?** I am solving Imaging problem.It is provides benefit over TF but not as much expected ### 11. Decent for a beginner **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Medical Devices | Small-Business (50 or fewer emp.) **Reviewed Date:** August 15, 2019 **What do you like best about TFLearn?** The best thing about TFLearn is it's seamless experience with graph visualizations showing all the details about weights, gradients and activations. **What do you dislike about TFLearn?** It's been seamless so far and there is nothing I dislike. **What problems is TFLearn solving and how is that benefiting you?** I have been trying to build a neural network to detect ischemia using MCG data and the benefits of using TFLearn is that I do not have to scratch my brains around code syntax which allows me to focus more on the research aspect. ### 12. If you are not expert in machine learning and want to start somewhere, TFLearn is the best **Rating:** 4.5/5.0 stars **Reviewed by:** Ahmad A. | Research Assistant , Small-Business (50 or fewer emp.) **Reviewed Date:** November 04, 2018 **What do you like best about TFLearn?** It is very easy to learn. It is higher-level API to TensorFlow and makes building up a machine learning model much faster and easier with less complications. **What do you dislike about TFLearn?** The explanations on its website about different parts and models and libraries is way far from being comprehensive, In most of the cases, a feature is just explained with few lines. **Recommendations to others considering TFLearn:** Do not just use the library as a black box, but also try to read and understand the modules of the library, it is easy to understand and will help you gain confidence in changing something in the functions of the library, in case needed **What problems is TFLearn solving and how is that benefiting you?** As a researcher and engineer, it gave me the ability to easily integrate my medium knowledge of machine learning into the real life application that I needed. ### 13. Very high speedy and high level **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) **Reviewed Date:** August 23, 2019 **What do you like best about TFLearn?** I liked the transparency over Tensorflow, the powerful helper functions with support of multiple inputs, outputs and optimizers, and mostly the beautiful visualization support. **What do you dislike about TFLearn?** I found it a little bit hard to use multiple gpus. **What problems is TFLearn solving and how is that benefiting you?** I've solved a multiclass business classification problem using TFLearn. I found its visualization support very beneficial. ### 14. Tflearn Review **Rating:** 3.0/5.0 stars **Reviewed by:** Verified User in E-Learning | Small-Business (50 or fewer emp.) **Reviewed Date:** August 28, 2019 **What do you like best about TFLearn?** Syntax are easier and cleaner. Faster and transparent. Visualization is great. **What do you dislike about TFLearn?** Not able to install in Windows. Few more tutorials will be really helpful. **Recommendations to others considering TFLearn:** Great for deep learning models. Easier to implement. Great visualization. **What problems is TFLearn solving and how is that benefiting you?** Classification problem in Natural Language Processing. Visualization of network is helpful for understanding. ### 15. learning TF **Rating:** 2.5/5.0 stars **Reviewed by:** Verified User in Research | Small-Business (50 or fewer emp.) **Reviewed Date:** August 11, 2019 **What do you like best about TFLearn?** I am not a heavy user of TF but I know working with TF is not as easy as other tools and TFLearn has tried to abstract things out **What do you dislike about TFLearn?** I haven't used it much to be able to say how it's better or worst than TF **What problems is TFLearn solving and how is that benefiting you?** I used the manual to learn tensorflow. ### 16. I have started exploring TF from last 6 months **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Information Services | Small-Business (50 or fewer emp.) **Reviewed Date:** August 24, 2019 **What do you like best about TFLearn?** Powerful Tool. Pretty good for Deep Learning. **What do you dislike about TFLearn?** No Support for Windows. TensorFlow lacks behind in both speed and usage when compared to its competitors **What problems is TFLearn solving and how is that benefiting you?** Great Tool for Deep Learning. ### 17. Great **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Enterprise (> 1000 emp.) **Reviewed Date:** August 27, 2019 **What do you like best about TFLearn?** TFLearn is a very useful tool to have in your Machine Learning toolkit **What do you dislike about TFLearn?** Integration with a third party application **What problems is TFLearn solving and how is that benefiting you?** Tensorflow ### 18. Good but not that great **Rating:** 2.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** November 24, 2018 **What do you like best about TFLearn?** A good higher level abstraction for using deep learning models out of the box. Saves the headache of having to create a manual configuration from scratch in tensorflow (other than if you want to use the Estimator API, which isn't that configurable). If I need to test a new architecture for my business-case, this can easily spin up one for me, the default configurations are quite usable. **What do you dislike about TFLearn?** Quite a few things, firstly why hasn't this merged with Tensorflow yet? Why is there no one addressing Github issues promptly? This is one of the few opensource libraries with over 500 open issues most of which seem to be legit on opening manually, and no one but the developer can address it as its not a usage doubt, but a bug. **Recommendations to others considering TFLearn:** If you want easy and speedily available test networks, go for it but in the long run more stable networks on the original tensorflow will be better. **What problems is TFLearn solving and how is that benefiting you?** Trying out deep learning models wasn't easier ever. TFLearn can give a workable solution very easily and its graph visualization helps in explaining the technical process to non-technical beneficiaries very conveniently. I was very much used to sklearn's API and now seeing something similar for tensorflow is like a win-win situation where I get the ease of a consistent API and power of the new Tensorflow library. ### 19. good framework to start with **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** November 09, 2018 **What do you like best about TFLearn?** simple abstraction on tensorflow, much easier to use than tf **What do you dislike about TFLearn?** not as powerful than tensorflow in terms of functionality **What problems is TFLearn solving and how is that benefiting you?** machine learning ### 20. Amazing if you are new in the field of ML **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Research | Enterprise (> 1000 emp.) **Reviewed Date:** November 09, 2018 **What do you like best about TFLearn?** It is a high level interface on the top of tensorflow, so if you don't want to spend days dealing with TF at the beginning, TFLearn is the best **What do you dislike about TFLearn?** the toturial is very brief, it needs more information about the library **What problems is TFLearn solving and how is that benefiting you?** I solve machine leaning problems in engineering applications - [View TFLearn pricing details and edition comparison](https://www.g2.com/products/tflearn/reviews?section=pricing&secure%5Bexpires_at%5D=2026-06-11+20%3A11%3A26+-0500&secure%5Bsession_id%5D=7da98c2d-47c3-4ba9-8a2b-a87374a7954b&secure%5Btoken%5D=21b899ee4b6e62f6c3d984dca3b96ad4177a34a23baa79f7271a1b2b40b00df8&format=llm_user) ## TFLearn Features **Core Functionality - Artificial Neural Network** - Neural Network Training - Neural Network Testing - Model Evaluation - Compliance **Data Handling - Artificial Neural Network** - Data Integration - Data Preprocessing **Performance - Artificial Neural Network** - Model Optimization - Scalability **Usability - Artificial Neural Network** - User Interface - Documentation & Support - Customizability **Advanced Features - Artificial Neural Network** - Deep Learning Capabilities - Transfer Learning - Real-Time Processing - Automated Model Tuning - Visualization Tools **Agentic AI - Artificial Neural Network** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Natural Language Interaction - Proactive Assistance - Decision Making ## Top TFLearn Alternatives - [Keras](https://www.g2.com/products/keras/reviews) - 4.6/5.0 (64 reviews) - [Microsoft Cognitive Toolkit (Formerly CNTK)](https://www.g2.com/products/microsoft-cognitive-toolkit-formerly-cntk/reviews) - 4.2/5.0 (22 reviews) - [DeepPy](https://www.g2.com/products/deeppy/reviews) - 4.1/5.0 (12 reviews)