Why TensorFlow is So Popular – Tensorflow Features
In this article, we will see Why TensorFlow Is So Popular, and then explore Tensorflow Features. TensorFlow is an open-source software library. It was originally developed by researchers and engineers working on the Google Brain Team within Google’s Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well!
Features of TensorFlow
- Models can be developed easily: TensorFlow supports high-level APIs, through which Machine Learning models can be built easily using Neural Networks.
- Complex Numeric Computations can be done: As the input dataset is huge, the mathematical computations/calculations can be done easily.
- Easy deployment and computation using CPU, GPU: TensorFlow supports training and building models on CPU and GPU. Computations can be done on both CPU and GPU and can be compared too.
- Contains pre-trained models and datasets: Google has included many datasets and pre-trained models in TensorFlow. Datasets include mnist, vgg_face2, ImageNet, coco etc.
- Pre-trained models for mobiles, embedded devices, and production: The Machine Learning models can be deployed on mobile and embedded devices using TensorFlow. Pre-trained models can be directly used for production.
- Tensorboard, a kit using TensorFlow’s visualization toolkit made ML easy through model graphs: Tensorboard is TensorFlow’s visualization toolkit used to display images, graphs, etc.
- Supporting Keras: Keras is a high-level API of TensorFlow that is built on top of TensorFlow and Theano. Nowadays, Keras has become popular as a widely used TensorFlow API.
- Open Source: TensorFlow is an open-source platform, free to use and allows developers and researchers to build and deploy Machine Learning models.
Why TensorFlow is popular?
- TensorFlow made Machine Learning easy: With pre-trained models, data, and high-level APIs, it has become easy for everyone to build ML models.
- Mostly used by researchers: Most of the researchers and students use TensorFlow in their research and model building.
- Ready-made models for production purposes: TensorFlow supports pre-trained models which can be used instantly for production and experiment.
- Using TensorFlow, ML is used as a service: Machine Learning has become a service with the help of TensorFlow. One can use the model required from the TensorFlow models.
- Used by many companies: TensorFlow is used by many companies, like Google, Intel, DeepMind, Twitter, Uber, DropBox, AirBnb, etc. More than 400 companies are using TensorFlow.
Applications and uses:
- Image and Face recognition
- HealthCare related applications like cancer, tumor detection, etc
- Recommendation Systems
- Virtual Assistants
- Self-driving cars
- Natural Language Processing