Google released TensorFlow as an open source technology in 2015 under an Apache 2.0 license. Since then, the framework has gained a variety of adherents beyond Google. For example, TensorFlow tooling is supported as add-on modules to machine learning and AI development suites from IBM, Microsoft...
Using the TensorFlow architecture, training is generally done on a desktop or in a data center. In both cases, the process is sped up by placing tensors on the GPU. Trained models can then run on a range of platforms, from desktop to mobile and all the way to cloud. TensorFlow also c...
TensorFlow is a Python-friendly open source library for developing machine learning applications and neural networks. Here's what you need to know about TensorFlow.
Machine learning frameworks like Google’s TensorFlow ease the process of acquiring data, training models, serving predictions, and refining future results. Created by the Google Brain team and initially released to the public in 2015, TensorFlow is an open source library for numerical computation ...
tf.gradients(), when used on complex numbers, erroneously flips the sign of the imaginary part: >>> x = tf.Variable(0. + 0.j) >>> sess.run(tf.gradients(x*x, x), feed_dict={x:0.1j}) [-0.20000000000000001j] >>> sess.run(tf.gradients(tf.exp...
For those who want to experiment with such use cases, Keras is a popular open source library, now integrated into the TensorFlow library, providing a Python interface for RNNs. The API is designed for ease of use and customization, enabling users to define their own RNN cell layer with cust...
ML.NET runs on Windows, Linux, and macOS using .NET, or on Windows using .NET Framework. 64 bit is supported on all platforms. 32 bit is supported on Windows, except for TensorFlow, LightGBM, and ONNX-related functionality. The following table shows examples of the type of predictions tha...
Learn what is fine tuning and how to fine-tune a language model to improve its performance on your specific task. Know the steps involved and the benefits of using this technique.
What is the meaning of the word logits in TensorFlow? is a function that maps probabilities ([0, 1]) to R ((-inf, inf)) Probability of 0.5 corresponds to a logit of 0. Negative logit correspond to probabilities less than 0.5, positive to > 0.5....
the development of self-driving features for cars; and the implementation of AI-based systems that detect cancers with a high degree of accuracy. The first generative adversarial network was developed, and Google launched TensorFlow, an open source machine learning framework that is widely used in ...