Why is TensorFlow so complicated?

For researchers, Tensorflow is hard to learn and hard to use. Research is all about flexibility, and lack of flexibility is baked into Tensorflow at a deep level. The declarative nature of the framework makes debugging much more difficult.

Is TensorFlow good for research?

Tensorflow is currently better for production models and scalability. It was built to be production ready. PyTorch is easier to learn and work with and, is better for some projects and building rapid prototypes.

Why is TensorFlow hated?

Tensorflow, by no means, has that flavor to it. It has a hostile interface, is really difficult to install on most machines and does some weird black magic every time you do “sess. run”. Add in an abnormally steep learning curve and you have everyone hating it.

Why Most researchers are shifting from TensorFlow to PyTorch?

“While some believe that PyTorch is still an upstart framework trying to carve out a niche in a TensorFlow-dominated world, the data tells a different story,” He writes. He speculates that researchers are switching to PyTorch in part because of its simplicity and available APIs.

How difficult is TensorFlow?

According to users of TensorFlow and industry-experts, TensorFlow is hard to learn and somewhat difficult to use too. Then check out the Artificial Intelligence course which includes TensorFlow within a training course of 32hrs with 48hrs of projects and exercises to help you gain the necessary hands-on experience.

Why is PyTorch better for research?

fact that PyTorch is python native, and integrates easily with other python packages makes this a simple choice for researchers. Many researchers use Pytorch because the API is intuitive and easier to learn and get into experimentation quickly, rather than reading through documentation.

Do researchers use Keras?

In general any tool that many researchers use is by definition useful/helpful. For the particular case of Keras and other neural network frameworks (like PyTorch, TensorFlow, etc), a lot of people use them.

Why is TensorFlow so popular?

Why TensorFlow is popular? TensorFlow made Machine Learning easy: With pre-trained models, data, and high-level APIs, it has become easy for everyone to build ML models. Mostly used by researchers: Most of the researchers and students use TensorFlow in their research and model building.

Is learning TensorFlow easy?

TensorFlow isn’t the easiest of languages, and people are often discouraged with the steep learning curve. There are other languages that are easier and worth learning as well like PyTorch and Keras. It’s helpful to learn the different architectures and types of neural networks so you know how they can be used.

Is TensorFlow certification easy?

Become a Tensorflow Certified Developer — It’s easier than you think! Starting out in Data Science and Machine Learning is still difficult because of the different approaches one can take and are suggested. Even more difficult is having to prove your proficiency to potential clients and recruiters.