Last updated on February 28th, 2021 at 12:03 pm
Are you searching for the best TensorFlow alternatives? Confused about choosing the best one? If yes, then you are in the right place now! Here today, we are going to help you to find out the ten best alternatives of TensorFlow.
Before that, it’s necessary to understand what is TensorFlow and its importance? Let’s know in detail.
TensorFlow is an advanced library system that assists in machine learning and AI (artificial intelligence) to improve the search engine’s excellence. In 2015 this end-to-end open-source, cross-platform library was developed by Google.
Now let’s understand what machine learning is and the types of machine learning!
So, the machine learning system is nothing but a special kind of platform where we can examine data, collect accurate information, and make the proper decision. Usually, machine learning comprises the machine learning library and bundles of algorithms. These are basically of three types like
Let’s back to the point and discuss the importance of TensorFlow!
TensorFlow’s importance is that it offers automatic suggestions on a large scale, which is not possible on any search engine.
Here we are going to list ten such top-class apps like tensorflow you will get in the market
Best alternatives of TensorFlow
Mlpack is one of the popular machine learning software you can use as a tensorflow alternative. This platform offers a user-friendly interface and offers easy access to users with better suggestions. You will always get the strong performance and high flexibility ability in this software.
Mlpack was released in 2008 and got popular within a few days because of its advanced features and easy to use interface. It offers LSTM structures, template classes of GRU. Most of the researcher and engineers uses this software to collect huge and accurate data for their projects.
Darknet is one of the best and relatively new machine learning software that is popular among people. This is an open-source library based on a neural network framework.
This software runs on C and CUDA programming language, which supports the CPU and GPU. Due to its fast, easy installation library and advanced feature, most people like this platform.
CatBoost is another top competitor of tensorflow in the current market. This is an open-source and decision tree library platform which can provide accurate and best data for the researcher. CatBoost was released in 2017, and Yandex researchers developed it.
This is a machine learning software that runs on programming languages Java, C++, and Python.
CatBoost is a high performing fast and reliable gradient booster library that supports both GPU and CPU. This platform is super accurate and easy to customize the functions.
Theano is one of the best open-source machine learning library systems you can use. The University of Montreal, Quebec, developed this software. It runs on Python and CUDA programming languages and is well compatible with three platforms like Microsoft Windows, macOS, and Linux.
This platform is handy for optimizing complicated mathematics expressions. You can say it’s beneficial, especially for matrix calculations. However, it’s hard to learn Theano directly as it is intense in learning, but Python has recently launched a straightforward project for Theano learners. There you can quickly learn everything efficiently due to the simple data structure.
Keras is another top class and highly recommended open-source neural network library you can use as TensorFlow alternatives. The best part of Keras is you can use it on your mobile phone as it supports both the android and iOS platforms.
With will get the feature of best cognitive load reduction practices with excellent extensibility. With this software, you can combine and create new modules like optimizer, cost functions, and neural layers. Keras also supports TPU and GPU, specifically in combination with CUDA.
If you need an alternative to tensorflow then Torch is always a better option for you. This is an advanced open-source machine learning framework. This software is specially designed for scientists. It runs with LUA programming language and is licensed under BSD.
The Torch was published in the year 2002 and got massive attention because of its unique features. This machine learning platform always offers deep algorithms and uses scripting programming languages like C and LuaJIT.
Torch provides a flexible N dimensional commanding array and extensively supports GPU. Overall, you can say this is an efficient language and easy to understand. This language is programmed by Ronam Collobert, which is very easy to use.
Infer.Net is one of the premium class model-based machine learning platform. This was released by Microsoft in the year 2008 and got popular within no time. The supportive language of Infer.Net is C, and this is a cross-platform library.
This library of the software is based on the high-performance code framework and is operated in an operating system like Linux, macOS, and windows.
Users can get several important features like real time data, approximate determination, substantial scalability, and much more on this platform. When it comes to the license, infer.NET is licensed under MIT.
Sciket Learn is a top-notch free to use machine learning module for Python built on SciPy. If you search for excellent software for data analysis and data mining, this is one of the most effective tools. You can use this tool for both personal and commercial purposes because it comes with a BDS license.
With this software’s help, users can efficiently conduct different tasks under different categories like preprocessing, model selection, clustering, and much more.
Sciket Learn is famous for its extensive use, and surprisingly many big brands of different industries are using this platform for hotel bookings and music streaming. Any user can integrate algorithms on this platform according to the need of their application, which is always a great feature you will find in Sciket Learn.
If you are looking for the best tensorflow competitors, we will suggest you go with Training Mule. This is a leading platform that can solve API-led connectivity and create an application network for apps, devices, and data on cloud and premises.
This is an advanced hybrid integration platform that includes API management, iPaaS, ESB, publish, and design. This is a user-friendly platform that helps to reduce the development and integration time. On the other hand, here, you can find data transformation is straightforward and meets the industry standard.
Though the enterprise edition of this platform and support cost is high, btw it’s worth it. Training Mule is also known as MuleSoft training, and it runs Java programming-based library.
When it comes to machine learning service providers, no doubt, Cloud AutoML comes to everyone’s mind. Cloud AutoML is a popular platform provided by Google.
This software always assists developers with limited machine learning knowledge to create high-end models as per the business requirements. This software also offers a free version with limited features.
Cloud AutoML is very popular among users because of its fast and accurate. This library is handled by Google’s state of art transfer learning and architecture search technology.
We have suggested all of the famous and advanced tensorflow alternatives in this post. When it comes to choosing the best one, it depends on you and your requirement. Each platform has its benefits and cons. So, go for the best one as per your need and budget. We hope this post will help you to pick up the best machine learning platform. If you have any doubts, feels free to ask us under the comment section, we will love to answer you anytime; thanks.
Frequent Asked Questions
What is TensorFlow?
What is TensorFlow used for?
TensorFlow is the library that helps you to build models. It is a useful platform for developers and designers. This app simplifies the task of machine learning. You can also learn how to solve the problems of machine learning such as perception, discovering, classification, creation and prediction.
What is better than TensorFlow?