Train your models with TensorFlow

Every tech enthusiast wants to master the complex discipline of Machine Learning. Acquiring and training datasets to allow a computer to learn patterns and make decisions accordingly can be overwhelming sometimes if you don’t know an easy way around.

Google came out with a solution and called it TensorFlow. It is an open-source machine learning framework used to tackle and implement some tricky large-scale machine learning and neural networking models to make the job of predicting future results easier. A part of

ML models that use multi-layer neural networks are called deep learning. It was developed to boost Google’s deep neural network research and can now be seen in the advanced Google search suggestions. The search engine giant with the largest set of data in the world needed some efficient way to scale up to massive models and algorithms.

TensorFlow was launched in 2017 and the current version stands at 2.2. TL has undergone several changes since it was first offered to the public. Some of the changes include added support for deep learning in computer graphics and discontinuation of support for Python 2.

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