Python is probably the most flexible languages you can find anywhere. And we say that not just because we think so. There have been multiple occasions where Python hasn’t failed to fascinate us by flaunting what it can do. And we can see that from its applications in Data Science (from handling huge amounts of data), Data Analysis and to using Artificial Intelligence models.
An Introduction to Python
As we already discussed, Python is a really flexible language. In 1991, Guido Van Rossum created it. And after its release, so many libraries have come into existence. These libraries provide you with so much more pliable, but their applications are yet unknown.
Of course, some of the major applications lie in Machine Learning, developing Artificial Intelligence Models, Data Analysis and Data Science. Let us discuss more about the key factors of Python for the same.
A Step towards Innovating with Python
Artificial Intelligence is a very vast field where Python helps out a lot. It isn’t just because of the ease of use of Python. Python has a huge amount of libraries that can help with Artificial Intelligence.
Some of which include:
• MLPack
• Scikit-learn
• TensorFlow
• SciPy
• PyTorch
• ML.NET
• Theano
Apart from using the languages for Artificial Intelligence, you can also use them for Data Science and Data Analysis. There have been so many unprecedented advancements in developing Artificial Intelligence models that can help the Automotive Industry.
Artificial Intelligence Models
Companies like Motional are working with Hyundai to develop their own Autonomous cars. They use Light Detection and Ranging (a remote sensing method) for their models. You can observe it in their latest model of Robotaxi – IONIQ 5.
Apart from this, Driive.ai, Nutonomy, AutoX and so many more companies have made advancements using AI Models to develop their cars.
NN (Neural Networks) in Automotives
PyTorch has helped build many Neural Networks as well. Artificial Neural Networks have their own field of applications. Deep Neural Networks, Convolutional Neural Networks and Recurrent Neural Networks can reinforce the development of Autonomous cars greatly.
Problems with Python for Decisions
The problem with Artificial Intelligence is their moral decision making. Even if an AI model learns how to drive a car by the reactions, codes and logic that we teach it, it will be bound by that same logic. Meaning the logical decision making is hindered.