Having an online presence and efficient technological systems is now becoming indispensable for businesses. As the need for efficient software applications continues to grow, so does the corresponding need for people with coding and related skills. The Python programming language and the Torch machine learning library are popular coding components. Both have enjoyed widespread acceptance and application since they were developed.
So what is the relationship between Python, Torch and PyTorch when it comes to coding skills? The answer is not far away.
PyTorch Explained
PyTorch is a popular open-source deep learning framework that first emerged in October 2016 via researchers at Facebook's Artificial Intelligence Research (FAIR) lab. It is called PyTorch because it is written in the Python programming language but based on the Torch Library. Writing it in Python ensures greater accessibility to the Python-centric deep learning community. Pytorch 2.4 is the latest version of the software.
PyTorch Uses and Relevance
“Google recognises the impact of PyTorch on the AI community, providing researchers and developers with powerful, flexible tools for innovation... We look forward to continuing our support for PyTorch and fostering an open ecosystem that accelerates machine learning research and application.” – Dwarak Rajagopal, Senior Engineering Director at Google
PyTorch has been described as a ‘research-focused framework’. It presently ranks among the most widely used deep learning frameworks, especially within the research community. Many researchers prefer PyTorch for new models and algorithm prototyping due to its quality features. Among these features are a user-friendly interface and dynamic computational graphs (DCGs).
Unlike static frameworks such as TensorFlow, PyTorch utilises dynamic DCGs to ensure more flexible, imperative development without having to compile the models prior to each execution. DCGs are particularly important when modelling natural language processing (NLP) tasks due to the possibility of each input yielding a different graph structure.
Here are some organisational use cases of PyTorch:
Stanford University is using PyTorch’s flexibility to efficiently research new algorithmic approaches
Wadhwani AI uses PyTorch To empower cotton farmers in India
Blue River Technology uses PyTorch for its ‘See & Spray’ solution
Lyft uses PyTorch to power machine learning for their self-driving cars
Disney uses PyTorch for animated character recognition
AstraZeneca is using PyTorch-powered algorithms to discover new drugs
Amazon Ads uses PyTorch and AWS Inferentia to scale models for ad processing
PyTorch regularly releases updates that include new features and enhancements that seek to address the increasing needs of a thriving AI community. In a nutshell, PyTorch is a powerful tool which AI and ML businesses can leverage to build and train models capable of playing key roles in solving complex problems, improving processes, and driving innovation.
Guide to Learning and Using PyTorch
Lots of resources are available out there for anyone wishing to add PyTorch to their skillset. You’ll find many of these resources on the PyTorch website. For example, the website has a ‘Learn the Basics’ tutorial that covers areas such as:
Quickstart
Tensors
Datasets and DataLoaders
Transforms
Build Model
Automatic Differentiation
Optimization Loop
Save, Load and Use Model
According to PyTorch developers, if you are already conversant with other deep learning frameworks, then the Quickstart area should be your first port of call. Quickstart will familiarise you with PyTorch’s API. If you’re a deep learning frameworks newbie, then your first destination should be the Tensors section where you’ll get a step-by-step guide.
Additionally, you can also check out other websites offering tutorials and online courses that teach PyTorch. Read as many PyTorch books as possible. Books are a rich source of knowledge for both newbies and experienced programmers. Join online PyTorch communities to network and learn.
Career Prospects With PyTorch Skills
As more organisations embrace ML and AI, there is a growing demand for PyTorch-savvy professionals for roles that offer competitive rewards and exciting career paths. Learning PyTorch is not just about understanding a tool but also about acquiring valuable skills that can help you start a career in a variety of industries. Knowledge of PyTorch will strengthen your grasp of ML and AI concepts while improving your data management and problem-solving abilities. So what will someone with a PyTorch skill likely earn in a year? According to Payscale, you can earn thousands of dollars annually with a PyTorch software library skill in the US, (as of August 1 2024). See more details on this below.
PyTorch is a powerful tech skill that is creating significant excitement in the world of AI and ML. If you want to settle for or change to a career that involves coding, software development and related fields, then PyTorch is definitely one skill you should consider acquiring.
