This repository will contain Tensorflow tutorials on a lot of the most popular deep learning concepts. It'll also contain some experiments on cool papers that I read. Hopefully, the notebooks will be ...

Differential privacy is a framework for measuring the privacy guarantees provided by an algorithm. Through the lens of differential privacy, we can design machine learning algorithms that responsibly ...

Machine learning couldn’t be hotter, with several heavy hitters offering platforms aimed at seasoned data scientists and newcomers interested in working with neural networks. Among the more popular ...

Machine learning is a complex discipline but implementing machine learning models is far less daunting than it used to be. Machine learning frameworks like Google’s TensorFlow ease the process of ...

One notable improvement is the added support for Python 3.12, showing TensorFlow's effort to stay current with the latest language releases. Google's TensorFlow, a leading open-source software library ...

The tuning of a pre-trained model is a crucial application for transfer learning in machine learning. It is a process of learning to re-adjust initially pre-trained models, with some big datasets, to ...

TensorFlow has become the most popular tool and framework for machine learning in a short span of time. It enjoys tremendous popularity among ML engineers and developers. According to the Hacker News ...