Google has been investing heavily in artificial intelligence (AI) over the last few years. While it announced a host of AI products at the Google I/O 2023, the tech giant has been involved in AI research and development for more than a decade. Under the umbrella of Google AI, Google Brain was a deep learning artificial intelligence research team formed in 2011 and one of its most prominent projects was TensorFlow, an open-source library that empowers software engineers and data scientists.
TensorFlow is a free and open-source library that provides data scientists and software engineers with an extensive range of tools to aid in building, training, and working with deep learning models.
Across several domains, Tensorflow has streamlined the process of developing and training machine learning models.
While it streamlines the developing process, TensorFlow requires a learning curve with adept knowledge of machine learning concepts and techniques. Users must be familiar with loss functions, model types, epochs, and cross-entropy loss to fully utilize it. Moreover, training machine learning models is a meticulous task and it requires massive amounts of labeled input data, thus making it a very detail-oriented process.
TensorFlow is capable of creating advanced analytics applications and this is one of its strongest points. The platform constructs models using data flow graphs and can also be used to develop large-scale neural networks. Thus, it can accomplish a wide range of tasks beginning from classification, perception, and understanding to discovery, prediction, and creation.
TensorFlow also features voice and image recognition technology for dealing with real-world scenarios. The machine learning models use image recognition
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