The great thing about the deep learning industry is that there are many libraries and frameworks you can use to simplify the job. Deep learning frameworks are almost ubiquitous, but it is crucial to know which ones to use for your deep learning models. The deep learning frameworks you choose can be the difference between your project succeeding or failing. On top of that, you also have the option of doing deep learning with python. Python offers many advantages over the competition because it is an easy-to-learn language for machine learning practitioners.
What is a deep learning framework? It is simply a set of libraries and tools that make building deep learning models easier. You can do things like deep reinforcement learning with relative ease because of the various code that has already been provided for you. Frameworks make the job of creating a successful model fast and easy. It also means you never need to reinvent the wheel by doing basic deep learning jobs from scratch.
Tensorflow – Best of the Deep Learning Frameworks
Tensorflow is one of the most famous deep learning frameworks on the Internet. It makes it possible to do deep learning with python relatively easily, and you can build your deep learning models with a code base that has been proven and tested. Tensorflow was developed by Google for its search engine products. Google also created a TPU, but that is not available commercially.
Tensorflow is useful for sound recognition, image recognition, video analysis, and even text applications. You can think of it as the Swiss Army knife of deep learning frameworks. You can build deep learning models in a variety of ways with this versatile framework. It also does deep reinforcement learning relatively easily as well. Finally, it offers GPU integration, meaning you can train deep learning models fast.
PyTorch is the Facebook competitor to Tensorflow in terms of deep learning frameworks. PyTorch is getting a lot more coverage lately, and many people think that it will eventually take over the number one spot from Tensorflow. People love this framework because of how flexible it is. It allows you to build deep learning models with python.
PyTorch gives you the option of building computational graphs as you go, and you can even make runtime changes to them as well. It is good for image detection and classification along with text work. For example, your natural language processing jobs can be done with this framework. It can also be used for deep reinforcement learning.
The Other Deep Learning Frameworks to Know
While these two frameworks are the most popular, you have other options to think about as well. The other deep learning frameworks are useful in a variety of areas, but they make it possible for you to do the job of building deep learning models on the cheap.
These deep learning frameworks also speed up the process of going from an idea to a finished project without having to do a lot of the grunt work required. Here is a list of the deep learning frameworks you should know:
Deep learning frameworks will only improve with time. The good thing for you is that your deep learning models will be easier to create in the future.