why Machine Learning is on its last legs?

In the world of machine learning, Tensorflow is one of the most popular frameworks. Recently, however, its use has begun to decline.

As the world of machine learning technology continues to evolve, the emphasis is increasingly on the use of open source tools. TensorFlow is one of these leading tools for machine learning on Python, but its popularity has recently declined.

Machine learning Python: is Tensorflow in danger of losing its place?

Tensorflow is a open source machine learning framework for Python, developed by Google. It is considered one of the most effective frameworks for machine learning, particularly for deep learning.

Tensorflow is still used in many applications production and research applications, including speech recognitionthe computer visionthe automatic translation and the content generation.

However, Google’s framework is beginning to suffer from a lack of improvement. Indeed, Tensorflow has remained in the models large size. This means that requires greater computing power. The problem is that most research institutions, such as universities, do not necessarily have the infrastructure to support this level of power.

Nowadays machine learning APIs are generally developed for Python with an intuitive integration line. Unfortunately, this is not the case with Tensorflow. Google’s API is heavier and more complex than its main competitor. Pytorch.

Pytorch could soon dethrone Tensorflow

Tensorflow and Pytorch are two of the most popular machine learning frameworks used by developers today. Tensorflow is an open source library which provides a complete set of tools for creating and training neural networks. Pytorchfor his part, is a deep learning framework developed by Facebook, which allows developers to create and manage rapidly deploy practical models. Both frameworks have become popular in recent years due to their ease of use and powerful capabilities.

However, as the machine learning space continues to evolve, Tensorflow is beginning to age in comparison with Pytorch. This is because Pytorch presents a more intuitive learning scheme for both beginners and experienced users. What’s more, Pytorch’s API is the closest to standard Python syntax.

What are the forecasts for machine learning technology?

Currently, the trend in machine learning technology is leading to a fairly transparent forecast. On the one hand, the use ofdistributed machine learning will continue to increase. It will allow us to continuously increase performance and reduce computation times.

On the other hand, the deployment ofmachine learning on on-board devicessuch as smartphones, will become increasingly common. Indeed, the advancement of mobile technology will strengthen application development exploiting machine learning. These applications include, for example, voice recognition, visual monitoring or intellectual assistance.

In addition, thereal-time machine learning will be increasingly used for applications such as recommendations, anomaly detection and control systems.