Tensorflow is a Python-friendly, open source, and end-to-end platform for deep learning and machine learning. The library is capable of training deep neural networks for image recognition, digit classification that is handwritten, word embedding, and recurrent neural networks. It also supports prediction at scale with the training models. Tensorflow further integrates a number of APIs for creating architecture of deep learning such as Recurrent Neural Network (RNN) and Convolutional Neural Network (CNN).
The blog here offers a detailed overview of the popular ML library.
Tensorflow offers professionals and developers the ability to create graphs and structures for describing data insights. The tool accepts inputs from the multi dimensional array aka Tensors which are then displayed through operational flowcharts.
Tensorflow is used for solve real life problems and is very easily accessible by the programmers. Needless to mention, it is a widely used tool in the data analytics domain.
Tensorflow has gained popularity mainly due to computational graphs, adaptability, and automatic differentiation. Some of the advantages of Tensorflow are as below:
Despite its widespread popularity, Tensorflow is not short of competitors. Here is a list of the popular competitors of Tensorflow:
Tensorflow is the open source library that carries out numerical computation and uses data flow with a flexible architecture. The ability to easily build ML models makes TensorFlow a staple library in the data science domain.
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