Apart from Tensor and Theano, there are quite a lot of other frameworks available in the market. For forward + backward, it seems that Theano > Torch > TensorFlow. This framework is considered a good option for beginners since it is ideal for learning and prototyping basic concepts. All the researches that urge the graphical flow for the implementation of artificial intelligence leverage these libraries. For each and every user, there is something out there in the market; if not, then there are developers who are offering customized frameworks for your businesses. It is mostly used in extensive research-based tasks, deep learning tasks, and also for defining, optimizing and evaluating different mathematical operations. Pytorch is a Python version of Torch, which was developed by Facebook in 2017. It is based on the languages of Python and C++ and is multi-GPU. In recent times, there has been an incline of various companies/businesses towards artificial intelligence. It is used to being the feature of artificial intelligence by making the use of python. It would be nearly impossible to get any support from the developers of Theano. Computational Network Toolkit (CNTK) is an open-source deep learning framework made by Microsoft. This library will work just with the python language and depends on python programming to get implemented. Theano was developed by Yoshua Bengio at Université de Montréal in 2007. © 2020 - EDUCBA. We have expertise in Machine learning solutions, Cognitive Services, Predictive learning, CNN, HOG and NLP. It is considered to have a clean and easily maintainable code. Tensorflow is capable to use one or more CPUs based on how it has to be performing. The main uses of Torch are machine learning, signal processing, parallel processing, computer vision, video, audio, image, and networking. However, Tensorflow tends to be the most famous deep learning framework today. TensorFlow Vs Theano Vs Torch Vs Keras Vs infer.net Vs CNTK Vs MXNet Vs Caffe: Key Differences It is known to achieve high performance due to its usage of Intel MKL/Intel MKL-DNN and multi-threaded programming in every Spark task. Theano is a completely python based library which means it has to be used with python only. -Both the frameworks provide parallel execution. -Theano is mostly used in carrying out Mathematical operations, whereas TensorFlow is used in voice/sound recognition, text-based applications, image recognition, time series, and video detection. Theano has been developed by the LISA group which is a part of the varsity of Montreal while Tensorflow has been developed by the Google Brain team for internal use. It is considered to be easy to set up as it has numerous sample codes and tutorials. One can simply pick these libraries to build the machine learning features enabled applications in a short span of time. TensorFlow Vs Theano An open source software library to carry out numerical computation using data flow graphs, the base language for TensorFlow is C++ or Python, whereas Theano is completely Python based library that allows user to define, optimize and evaluate mathematical expressions evolving multi-dimensional arrays efficiently, as per their website. It is considered to be faster than other Python-based frameworks. The market comprises of other frameworks too, apart from just TensorFlow and Theano. Privacy Policy and Terms of Use | Without any further ado, let's discuss these two, along with a few other frameworks. Similar to Theano, it can also be considered as the mathematical library that contributes to machine learning by the ability of computation it offers. However, they both provide CUDA support. Theano takes the Lead in Usability and Speed, but TensorFlow is … The platform for Torch is Linux, macOS, Windows, iOS, and Android. Companies that have been using TensorFlow include Google, Twitter, Uber, Snapchat, GE Healthcare, PayPal, and Dropbox, just to name a few. However, it can be a bit difficult to set it up in CentOS. Being able to serve in two languages, it is considered by the developers. You can also build arbitrary graphs of neural networks and parallelize them over CPUs and GPUs in the most efficient way possible. The following are some of the key differences that are mentioned below: Theano has been developed by the LISA group which is a part of the varsity of Montreal while Tensorflow has been developed by … It also supports data parallelism and contains many pre-trained models. Numerous other open-source deep libraries have been built on top of Theano, such as Keras, Lasagne, and Blocks. These include voice/sound recognition, text-based applications, image recognition, time series, and video detection. On the other hand, TensorFlow is still available in the market. Caffe is a general deep learning framework that is based on C++. In addition to this, it is capable of working with multiple CPUs. Theano is pretty famous with academic researchers, due to it being a deep learning library. Torch provides support and a wide range of algorithms for machine learning. The codes are written in Python on top of CUPY and Numpy libraries. The market comprises of other frameworks too, apart from just TensorFlow and Theano. These three provide high-level frameworks for fast prototyping and model testing. The Tensorflow library has been developed to work with C++ and python as well. Prominent companies like Airbus, Google, IBM and so on are using TensorFlow to produce deep learning algorithms. It is a scripting language program which was initially written in and offered on the Lua programming language but has now been ported to various other languages, such as Python (Pytorch) and C/C++. It contributes to artificial intelligence by introducing the use of data flow graphs. Theano vs. TensorFlow is a very vast topic with a lot of technical details attached to it. Tensorflow is the C++ and python based library that means it could be used in both, the C++ and the Python programming. What is Theano used for in machine learning? Tensorflow is another library that is free and open-source which could be used to implement dataflow in the program. The following are some of the key differences that are mentioned below: Below are the differences between Theanoa and Tensorflow. -TensorFlow has a faster compiling time than Theano, but the execution speed of TensorFlow is slower than Theano. Due to an increase in the use of Artificial Intelligence by various businesses/companies, deep learning framework developers are striving hard to launch quality frameworks into the market to fulfil the needs of various users and their companies. The battle of the frameworks- Theano vs. TensorFlow. Yangqing Jia is the creator of Caffe2, who now works at Facebook. Caffe2 is considered to be lightweight. Hence, we can easily say that TensorFlow is better than Theano. For each and every user, there is something out there in the market; if not, then there are developers who are offering customized frameworks for your businesses. -Theano is mostly used in carrying out Mathematical operations, whereas TensorFlow is used in voice/sound recognition, text-based applications, image recognition, time series, and video detection. With an increase in the trend of artificial intelligence, the market has been flooded with numerous deep learning frameworks. This makes it easy to spin up sessions and run the code on different machines without having to stop or restart the program. The CNTK has both low level and high-level API for building neural networks. Let's discuss this. It is efficient and user friendly due to the use of LuaJit, the scripting language, which provides maximum flexibility to the user. A deep learning library from Apache Stark. TensorFlow vs. Theano is a highly debatable topic. Which one is better? We are the Pioneers in the Computational Language Theory Arena  - Do you want to become a pioneer yourself ?Get In Touch. Theano has been developed by the LISA group and works perfectly fine but it is not as popular Tensorflow due to some of the limitations it has. By closing this banner, scrolling this page, clicking a link or continuing to browse otherwise, you agree to our Privacy Policy, Black Friday Mega Offer - TensorFlow Training (11 Courses, 3+ Projects) Learn More, 11 Online Courses | 3 Hands-on Projects | 55+ Hours | Verifiable Certificate of Completion | Lifetime Access, Java Training (40 Courses, 29 Projects, 4 Quizzes), Python Training Program (36 Courses, 13+ Projects), HTML Training (12 Courses, 19+ Projects, 4 Quizzes), Functional Testing vs Non-Functional Testing, High level languages vs Low level languages, Programming Languages vs Scripting Languages, Difference Between Method Overloading and Method Overriding.