QuAIT

 Quantum Computing   Quantum computing is a vicinity of reckoning focused on developing computer technology based on the principles of quantum physics.  Quantum physics is one among the foremost winning series of contemporary science describing the way our world works at the foremost elementary level.  Quantum computing has become one of the most leading applications of quantum physics. Quantum computers can solve some of the world’s impenetrable problems that are beyond the reach of even today’s most efficient supercomputers. We can assume that quantum computers are not going to replace classical computers but they are a radically different way of operation that enables them to perform calculations that classical computers cannot. Let’s see how they differ: Classical computers encode the information in bits and each bit can represent 0 or 1 that ultimately translate into computer functions to perform simple calculations. Unlike classical computers, quantum ...

 Abstract Quantum computers are designed to outperform standard computers by running quantum algorithms. Areas during which quantum algorithms are often applied include cryptography, search and optimisation, simulation of quantum systems and solving large systems of linear equations. Here we briefly survey some known quantum algorithms, with a stress on a broad overview of their applications instead of their technical details. We include a discussion of recent developments and near-term applications of quantum algorithms. Introduction A quantum computer may be a machine designed to use quantum physics to try to do things which can't be done by any machine based only on the laws of classical physics. Eventual applications of quantum computing range from breaking cryptographic systems to the planning of latest medicines. These applications are supported quantum algorithms—algorithms that run on a quantum computer and achieve a speedup, or other efficiency improvement, over any possib...

Libraries for Machine learning in Python Machine Learning is the study of computer algorithms that improves automatically through experiences. In the older days, people used to do the machine learning tasks manually coding all the algorithms, mathematical, and statistical formulae. This made the process, time- consuming, and inefficient. But these days it became very efficient by python libraries. Libraries have made coding easy and time-saving. Some of the python libraries used in machine learning: ● Numpy ● Pandas ● Scipy ● Scikit-learn ● Matplotlib ● Keras ● Tensorflow Numpy: Numpy stands for numerical python. It is used for working with arrays. Numpy is a very popular Python library for large multi-dimensional array and matrix processing, with the help of a large collection of high- level mathematical functions. It is very useful for fundamental scientific computations in Machine Learning. It is particularly useful for linear algebra, Fourier transform, and random number capabiliti...

Classification of animals using CNN Model In this model, we try to predict whether the animal is a dog or a cat. #We will use the Keras library to create our model. Keras: is an open - source library that provides a python interface for artificial neural networks. from keras.models import Sequential from keras.layers import Conv2D,Activation,MaxPooling2D,Dense,Flatten,Dropout import numpy as np #Let’s initialize a convolutional neural network using the sequential model of Keras. classifier = Sequential() # Adding Convolution Layer classifier.add(Conv2D(32,(3,3),input_shape=(64,64,3))) #Conv2D stands for a 2-dimensional convolutional layer. Here, 32 is the number of filters needed. A filter is an array of numeric values. (3,3) is the size of the filter, which means 3 rows and 3 columns. The input image is 64 64 3 in dimensions, that is, 64 height, 64 widths, and 3 refer to RGB values. Each of the numbers in this array (64,64,3) is given values from 0 to 255, which describes the pixel in...

 Is the Neural Network an algorithm? No. Neural Network is a mathematical model that works similar to human's intelligence. Artificial intelligence and machine learning haven’t just grabbed headlines and made for blockbuster movies; they’re poised to make a real difference in our everyday lives, such as with self-driving cars and life-saving medical devices. In fact, according to the Global Big Data Conference, AI is “completely reshaping life sciences, medicine, and healthcare” and is also transforming voice-activated assistants, image recognition, and many other popular technologies. Artificial Intelligence is a term used for machines that can interpret the data, learn from it, and use it to do such tasks that would otherwise be performed by humans. Machine Learning is a branch of Artificial Intelligence that focuses more on training the machines to learn on their own without much supervision. What is a neural network? If you are not familiar with these terms, then this neural ne...

Modular Neural Network A modular neural network is one that is composed of more than one neural network model connected by some intermediary. Modular neural networks can allow for the sophisticated use of more basic neural network systems managed and handled in conjunction. • MNN is a collective group of different networks working independently and contributing towards the desired outcome. • It enhances a unique quality of constructing networks and performing sub-tasks by breaking them. • The efficiency of this network is high compared to other networks because there are no inter-connected links between them. • Robustness is quite an advantageous factor in these networks. • Modular neural networks reduce a single large, unwieldy neural network to smaller, potentially more manageable components. • It reduces the complexity of the network into smaller components Issues Leading to Modular Networks: -> Reducing Model Complexity ->...