Artificial Intelligence is basically a branch of computer science and its main objective is to create intelligent machines which can work as similar as human beings. Through AI machines, you can perform numerous tasks like it can learn, plan, speech recognition, perceive and solve real queries.
Now let's talk about Artificial Intelligence with Python. So, as we all know that Python comes up with huge set of libraries and many libraries of Python are for machine learning and artificial intelligence. Artificial Intelligence with Python is very easy to learn and understandable. Nowadays, Python becomes the most favourite programming language as it is very powerful and easy to implement. Thus, in short we can say that learning Artificial Intelligence with Python is more beneficial rather than other programming languages.
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Nowadays, Artificial Intelligence becomes so important as it makes possible for machines to perform human-like tasks very easily. Artificial Intelligence is just equivalent to robotics. You can see live examples of AI in your surroundings like chess paying computers, self driving cars and much more. Artificial Intelligence is important in computer science to find an accurate file from millions of data within a few seconds.
AI use various libraries of Python for performing tasks quickly and easily. So, here is the list of Top 5 Python Libraries used for Artificial Intelligence.
1. TensorFLow: It is an open-source software that is used to compute numerical data using data flow graphs.
2. SciKit Learn: It is a very powerful library in python for artificial intelligence which is used to build models. It has so many in-built features like supervised learning algorithms, cross-validation and unsupervised learning algorithms.
3. Torch: It is also an open-source library for executing scientific and numerical operations. It has powerful N-dimensional array through which you can perform various operations like slicing and indexing.
4. Keras: It is a Python open-source neural network library. This library is user-friendly, extensible, works seamlessly with Theano and TensorFlow and can also efficiently on both CPU & GPU.
5. Theano: It is another powerful library of Python that allows you to perform numerical operations having multi-dimensional arrays. Also, it can easily optimized for CPU & GPU and very efficient for numerical tasks.
There are various factors one must keep in mind before selecting the correct programming language like ease of coding, fast to learn, portable, scalable and so on. There are so many programming languages that works really well with Artificial Intelligence such as C/C++, Java, LISP and Prolog. But the most recent addition to the list is Python.
So, here are some reasons, why Python is the most used language over other programming languages for Artificial Intelligence.
1. The vary first advantage of Python is that it renders good quality documentation.
2. In comparison to other programming languages, Python is easy and fast to learn.
3. Python has so many image intensive library tools for numeric and scientific applications like Python Imaging library, Numeric Python, Scientific Python, VTK & Maya 3D Visualization Toolkits and many other tools.
4. The most important factors required in language for AI applications is that it must be well designed, robust, fast, portable and scalable. And the best part is that all these factors are available in Python.
5. Lastly, Python is the open source language so you can make any change accordingly.
How AI works is equivalent to how does a human brain work or react on any particular situation. Now, the question arises how does it thinks or react on any situation?
Here in this blog, we are going to explain this in a simple manner.
1. Machine Learning in AI: Artificial Intelligence has an application that allows computer systems to automatically learn and improve from experience and that is machine learning. ML laid down emphasis on the making of algorithms which can analyze the data and make the predictions accordingly.
2. Deep Learning in AI: Deep Learning plays a vital role in Artificial Intelligence working by finding the single output from numerous inputs. For example: If you are searching for a particular file from millions of files available in the system. Then, deep learning helps you to find that particular file within a few seconds. Speech recognition is also an example of deep learning.
3. Neural Network is also important in AI as it enables deep learning. It helps in AI working by analyzing the data repeatedly to find associations and give meaning to undefined data too which is checked earlier. There are various models in Neural Network like positive reinforcement which is also essential in AI working. As via this model the machine is taught that it has correctly identified the object.
4. Cognitive Computing: this is another necessary component of AI that train machines to behave like humans and improves interaction between humans and machines as well. This component basically creates the human thought process in a computer model.
5. Natural Language Processing (NLP): NLP teaches machines to understand human language in context and gives logical answers. This component gives permission to computers to interpret, recognize and produce human language and speech.
6. Computer Vision: It is used to interpret the data by understanding the ../images which include graphs, pictures, tables, videos, etc. It is an integral field of AI that enables a system to identify, process and interpret visual data.
All these components help in AI working a lot and all are interrelated to each other. I think this blog is helpful for you to know about how does Artificial Intelligence works? If you want to read such blogs, then you can read our other blog topics as well.
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