The Go-To Friend for AI Programming
Python still remains a dominant force in AI development, with more than 275,495 companies using it.
Why PyTorch is Love
Google was leading with TensorFlow, but Meta’s PyTorch won hearts with the ease of use, and things have stayed that way
TensorFlow Releases New Update TF 2.12.0
Major improvements have been made to Keras as well.
Top 9 Python Libraries for Machine Learning in 2022
From data visualisation to deep learning libraries, Python is the most valuable language for machine learning.
Google AI Launches an Open Source Library to Store & Manipulate Large Multi-Dimensional Arrays
The library aims to address key engineering challenges in scientific computing through better management and processing of large datasets.
What’s New in the Latest TensorFlow 2.10
TensorFlow’s team is now introducing Decision Forests 1.0 with the latest release
A deep dive into image data preprocessing by TensorFlow
Preprocessing prevents from overfitting
How to accelerate TensorFlow models with the XLA compiler?
XLA is a compiler used to accelerate training time of Tensorflow models and reduce memory consumption.
Tensor2Tensor to accelerate training of complex machine learning models
This article mainly focuses on the Tensor2Tensor library and to understand the dynamic abilities to handle and process complex models.
Tensorflow Model Remediation- A framework for responsible AI
Tensorflow model remediation is a framework used to obtain fairness free and bias free models. It aims to produce robust models that is not affected by sensitive attributes of data.
Tensorflow weight clustering API – An optimization toolkit for heavy-weight models
The weight clustering API is one of the use cases of the Tensorflow model optimization library and it aims to optimize the models developed so that they can be easily integrated into edge devices.
TensorFlow Probability – A tool to build deep probabilistic models
This article has explained the importance of Tensorflow probability and its working principle. It has also explained the working principle of Tensorflow probability and its importance in the context of TensorFlow modelling.
