z Artificial Intelligence Interview Questions | Eklavya Online

z Artificial Intelligence Interview Questions

What are the Advantages of an Expert System?

The advantages of an expert system are: Easy availability Low production costs Greater speed and reduced workload They avoid motions, tensions, and fatigue They reduce the rate of errors.

What are artificial intelligence career domains?

A career in this can be realized within a variety of settings including : private companies public organizations education the arts healthcare facilities government agencies and the military.

What is Naive Bayes?

Naive Bayes Machine Learning algorithm is a powerful algorithm for predictive modeling. It is a set of algorithms with a common principle based on Bayes Theorem. The fundamental Naive Bayes assumption is that each feature makes an independent and equal contribution to the outcome.

What is a Turing Test? Explain.

A Turing test allows you to check your machine’s Intelligence in comparison to human Intelligence. In a Turing test, a computer would challenge human Intelligence, and if it passes the test, only then can you term it as intelligent. Even a smart machine might not be able to replicate humans also though it passes the …

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What is the Tower of Hanoi?

Tower of Hanoi essentially is a mathematical puzzle that displays how recursion is utilised as a device in building up an algorithm to solve a specific problem. The Tower of Hanoi can be solved using a decision tree and a breadth-first search (BFS) algorithm in AI. With 3 disks, a puzzle can essentially be solved …

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Why do we need Artificial Intelligence?

The goal of Artificial intelligence is to create intelligent machines that can mimic human behavior. We need AI for today’s world to solve complex problems, make our lives more smoothly by automating the routine work, saving the manpower, and to perform many more other tasks.

What are the different domains/Subsets of AI?

AI covers lots of domains or subsets, and some main domains are given below: Machine Learning Deep Learning Neural Network Expert System Fuzzy Logic Natural Language Processing Robotics Speech Recognition.

What is Artificial Intelligence?

is a field of computer science wherein the cognitive functions of the human brain are studied and tried to be replicated on a machine/system. Artificial Intelligence is today widely used for various applications like computer vision, speech recognition, decision-making, perception, reasoning, cognitive capabilities, and so on.

What’s selection bias? What other types of biases could you encounter during sampling?

When you’re dealing with a non-random sample, selection bias will occur due to flaws in the selection process. This happens when a subset of the data is consistently excluded because of a particular attribute. This exclusion will distort results and influence the statistical significance of the test. Other types of biases include survivorship bias and …

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Explain Alpha–Beta pruning.

Alpha–Beta pruning is a search algorithm that tries to reduce the number of nodes that are searched by the minimax algorithm in the search tree. It can be applied to ‘n’ depths and can prune the entire subtrees and leaves.

What is model accuracy and model performance?

Model accuracy, a subset of model performance, is based on the model performance of an algorithm. Whereas, model performance is based on the datasets we feed as inputs to the algorithm.

What’s your favorite use case?

Just like research, you should be up to date on what’s going on in the industry. As such, if you’re asked about use cases, make sure that you have a few examples in mind that you can share. Whenever possible, bring up your personal experiences. You can also share what’s happening in the industry. For …

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What is Artificial Intelligence?

Artificial Intelligence is an area of computer science that emphasizes the creation of intelligent machine that work and reacts like humans.

List some applications of AI.

Natural language processing Chatbots Sentiment analysis Sales prediction Self-driving cars Facial expression recognition Image tagging

What is a fuzzy logic?

Fuzzy logic is a subset of AI; it is a way of encoding human learning for artificial processing. It is a form of many-valued logic. It is represented as IF-THEN rules.

What conferences are you hoping to attend this year? Any keynote speeches you’re hoping to catch?

Conferences are great places to network, attend workshops, learn, and grow. So if you’re planning to stick to a career in artificial intelligence, you should be going to some of these. For example, Deep Learning World has a great one every summer. This year’s event in Las Vegas will feature keynote speakers like Dr. Dyann …

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What are some examples of AI in use?

Some compelling examples of AI applications are: Chatbots Facial recognition Image tagging Natural language processing Sales prediction Self-driving cars Sentiment analysis

What is vanishing gradient?

As we add more and more hidden layers, backpropagation becomes less useful in passing information to the lower layers. In effect, as information is passed back, the gradients begin to vanish and become small relative to the weights of the network.

What is an artificial intelligence Neural Networks?

Artificial intelligence Neural Networks can model mathematically the way biological brain works, allowing the machine to think and learn the same way the humans do- making them capable of recognizing things like speech, objects and animals like we do.

What does the language of FOPL consists of

a) A set of constant symbols b) A set of variables c) A set of predicate symbols d) A set of function symbols e) The logical connective f) The Universal Quantifier and Existential Qualifier g) A special binary relation of equality

What’s an eigenvalue? What about an eigenvector?

The directions along which a particular linear transformation compresses, flips, or stretches is called eigenvalue. Eigenvectors are used to understand these linear transformations. For example, to make better sense of the covariance of the covariance matrix, the eigenvector will help identify the direction in which the covariances are going. The eigenvalues will express the importance …

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List the applications of fuzzy logic.

Facial pattern recognition Air conditioners, washing machines, and vacuum cleaners Antiskid braking systems and transmission systems Control of subway systems and unmanned helicopters Weather forecasting systems Project risk assessment Medical diagnosis and treatment plans Stock trading

What’s a Turing test?

The Turing test, named after Alan Turing, is a method of testing a machine’s human-level intelligence. For example, in a human-versus-machine scenario, a judge will be tasked with identifying which terminal was occupied by a human and which was occupied by a computer based on individual performance. Whenever a computer can pass off as a …

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Define LSTM.

Long short-term memory (LSTM) is explicitly designed to address the long-term dependency problem, by maintaining a state of what to remember and what to forget.

What is an expert system? What are the characteristics of an expert system?

An expert system is an Artificial Intelligence program that has expert-level knowledge about a specific area and how to utilize its information to react appropriately. These systems have the expertise to substitute a human expert. Their characteristics include: High performance Adequate response time Reliability Understandability

What is a partial-order planning?

A problem has to be solved in a sequential approach to attain the goal. The partial-order plan specifies all actions that need to be undertaken but specifies an order of the actions only when required.

What is a recommendation system?

A recommendation system is an information filtering system that is used to predict user preference based on choice patterns followed by the user while browsing/using the system.

What does Partial order or planning involve?

In partial order planning , rather than searching over possible situation it involves searching over the space of possible plans. The idea is to construct a plan piece by piece.

Where do you usually source your data sets?

If you talk about AI projects that you’ve worked on in your free time, the interviewer will probably ask where you sourced your data sets. If you’re genuinely passionate about the field, you would have worked on enough projects to know where you can find free data sets.

What’s TensorFlow?

TensorFlow is an open-source framework dedicated to ML. It’s a comprehensive and highly adaptable ecosystem of libraries, tools, and community resources that help developers build and deploy ML-powered applications. Both AlphaGo and Google Cloud Vision were built on the Tensorflow platform.

What is an autoencoder? Name a few applications.

An autoencoder is basically used to learn a compressed form of the given data. A few applications of an autoencoder are given below: Data denoising Dimensionality reduction Image reconstruction Image colorization

What are the different algorithm techniques you can use in AI and ML?

Some algorithm techniques that can be leveraged are: Learning to learn Reinforcement learning (deep adversarial networks, q-learning, and temporal difference) Semi-supervised learning Supervised learning (decision trees, linear regression, naive bayes, nearest neighbor, neural networks, and support vector machines) Transduction Unsupervised learning (association rules and k-means clustering)

What is FOPL?

First-order predicate logic is a collection of formal systems, where each statement is divided into a subject and a predicate. The predicate refers to only one subject, and it can either modify or define the properties of the subject.

What methods are used for reducing dimensionality?

Dimensionality reduction is the process of reducing the number of random variables. We can reduce dimensionality using techniques such as missing values ratio, low variance filter, high correlation filter, random forest, principal component analysis, etc.

What are the different types of AI?

Reactive Machines AI: Based on present actions, it cannot use previous experiences to form current decisions and simultaneously update their memory. Example: Deep Blue Limited Memory AI: Used in self-driving cars. They detect the movement of vehicles around them constantly and add it to their memory. Theory of Mind AI: Advanced AI that has the …

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Why is game theory important to AI?

Game theory, developed by American mathematician Josh Nash, is essential to AI because it plays an underlying role in how these smart algorithms improve over time. At its most basic, AI is about algorithms that are deployed to find solutions to problems. Game theory is about players in opposition trying to achieve specific goals. As …

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What is an A* algorithm search method?

A* is a computer algorithm that is extensively used for the purpose of finding the path or traversing a graph in order to find the most optimal route between various points called the nodes.

What is Deep Learning?

Deep Learning is a subset of Machine Learning which is used to create an artificial multi-layer neural network. It has self-learning capabilities based on previous instances, and it provides high accuracy.

What is a breadth-first search algorithm?

A breadth-first search (BFS) algorithm, used for searching tree or graph data structures, starts from the root node, then proceeds through neighboring nodes, and further moves toward the next level of nodes.

When is it necessary to update an algorithm?

You should update an algorithm when the underlying data source has been changed or whenever there’s a case of non-stationarity. The algorithm should also be updated when you want the model to evolve as data streams through the infrastructure

What are the advantages of neural networks?

Require less formal statistical training Have the ability to detect nonlinear relationships between variables Detect all possible interactions between predictor variables Availability of multiple training algorithms

Can you name the properties of a good knowledge representation system?

From the perspective of systems theory, a good knowledge representation system will have the following: Acquisition efficiency to acquire and incorporate new data Inferential adequacy to derive knowledge representation structures like symbols when new knowledge is learned from old knowledge Inferential efficiency to enable the addition of data into existing knowledge structures to help the …

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What is a depth-first search algorithm?

Depth-first search (DFS) is based on LIFO (last-in, first-out). A recursion is implemented with LIFO stack data structure. Thus, the nodes are in a different order than in BFS. The path is stored in each iteration from root to leaf nodes in a linear fashion with space requirement.

What is TensorFlow?

TensorFlow is an open-source Machine Learning library. It is a fast, flexible, and low-level toolkit for doing complex algorithms and offers users customizability to build experimental learning architectures and to work on them to produce desired outputs.

Mention the difference between statistical AI and Classical AI ?

Statistical AI is more concerned with “inductive” thought like given a set of pattern, induce the trend etc. While, classical AI, on the other hand, is more concerned with “ deductive” thought given as a set of constraints, deduce a conclusion etc.

What’s regularization?

When you have underfitting or overfitting issues in a statistical model, you can use the regularization technique to resolve it. Regularization techniques like LASSO help penalize some model parameters if they are likely to lead to overfitting. If the interviewer follows up with a question about other methods that can be used to avoid overfitting, …

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What is artificial intelligence?

AI can be described as an area of computer science that simulates human intelligence in machines. It’s about smart algorithms making decisions based on the available data. Whether it’s Amazon’s Alexa or a self-driving car, the goal is to mimic human intelligence at lightning speed (and with a reduced rate of error).

Explain the different algorithms used for hyperparameter optimization.

Grid Search Grid search trains the network for every combination by using the two set of hyperparameters, learning rate and the number of layers. Then evaluates the model by using Cross Validation techniques. Random Search It randomly samples the search space and evaluates sets from a particular probability distribution. For example, instead of checking all …

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What is a heuristic function?

A heuristic function ranks alternatives, in search algorithms, at each branching step based on the available information to decide which branch to follow.

In Python’s standard library, what packages would you say are the most useful for data scientists?

Python wasn’t built for data science. However, in recent years it has grown to become the go-to programming language for the following: Machine learning Predictive analytics Simple data analytics Statistics For data science projects, the following packages in the Python standard library will make life easier and accelerate deliveries: NumPy (to process large multidimensional arrays, …

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What’s the difference between inductive, deductive, and abductive learning?

Inductive learning describes smart algorithms that learn from a set of instances to draw conclusions. In statistical ML, k-nearest neighbor and support vector machine are good examples of inductive learning. There are three literals in (top-down) inductive learning: Arithmetic literals Equality and inequality Predicates In deductive learning, the smart algorithms draw conclusions by following a …

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What is a bidirectional search algorithm?

In a bidirectional search algorithm, the search begins in forward from the beginning state and in reverse from the objective state. The searches meet to identify a common state. The initial state is linked with the objective state in a reverse way. Each search is done just up to half of the aggregate way.

What are intelligent agents?

An intelligent agent is an autonomous entity that leverages sensors to understand a situation and make decisions. It can also use actuators to perform both simple and complex tasks. In the beginning, it might not be so great at performing a task, but it will improve over time.

What is the lifetime of a variable?

When we first run the tf.Variable.initializer operation for a variable in a session, it is started. It is destroyed when we run the tf.Session.close operation.

What is the purpose of Deep Learning frameworks such as Keras, TensorFlow, and PyTorch?

Keras is an open source neural network library written in Python. It is designed to enable fast experimentation with deep neural networks. TensorFlow is an open-source software library for dataflow programming. It is used for machine learning applications like neural networks. PyTorch is an open source machine learning library for Python, based on Torch. It …

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What is collaborative filtering?

Collaborative filtering can be described as a process of finding patterns from available information to build personalized recommendations. You can find collaborative filtering in action when you visit websites like Amazon and IMDB. Also known as social filtering, this approach essentially makes suggestions based on the recommendations and preferences of other people who share similar …

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What’s the most popular programming language used in AI?

The open-source modular programming language Python leads the AI industry because of its simplicity and predictable coding behavior. Its popularity can be attributed to open-source libraries like Matplotlib and NumPy, efficient frameworks such as Scikit-learn, and practical version libraries like Tensorflow and VTK. There’s a chance that the interviewer might keep the conversation going and …

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How does face verification work?

Face verification is used by a lot of popular firms these days. Facebook is famous for the usage of DeepFace for its face verification needs. There are four main things you must consider when understanding how face verification works: Input: Scanning an image or a group of images Process: Detection of facial features Feature comparison …

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What is a top-down parser?

A top-down parser begins by hypothesizing a sentence and successively predicting lower level constituents until individual pre-terminal symbols are written.

Can you list some disadvantages related to linear models?

There are many disadvantages to using linear models, but the main ones are: Errors in linearity assumptions Lacks autocorrelation It can’t solve overfitting problems You can’t use it to calculate outcomes or binary outcomes

What is regularization in Machine Learning?

Regularization comes into the picture when a model is either overfit or underfit. It is basically used to minimize the error in a dataset. A new piece of information is fit into the dataset to avoid fitting issues.

What is a uniform cost search algorithm?

The uniform cost search performs sorting in increasing the cost of the path to a node. It expands the least cost node. It is identical to BFS if each iteration has the same cost. It investigates ways in the expanding order of cost.

What is a cost function?

A cost function is a scalar function that quantifies the error factor of the neural network. Lower the cost function better the neural network. For example, while classifying the image in the MNIST dataset, the input image is digit 2, but the neural network wrongly predicts it to be 3.

What are AI neural networks?

in AI mathematically model how the human brain works. This approach enables the machine to think and learn as humans do. This is how smart technology today recognizes speech, objects, and more.

What is the Minimax Algorithm? Explain the terminologies involved in a Minimax problem.

Minimax is a recursive algorithm used to select an optimal move for a player assuming that the other player is also playing optimally. A game can be defined as a search problem with the following components: Game Tree: A tree structure containing all the possible moves. Initial state: The initial position of the board and …

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What’s a feature vector?

A feature vector is an n-dimensional vector that contains essential information that describes the characteristics of an object. For example, it can be an object’s numerical features or a list of numbers taken from the output of a neural network layer. In AI and data science, feature vectors can be used to represent numeric or …

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How are game theory and AI related?

AI system uses game theory for enhancement; it requires more than one participant which narrows the field quite a bit. The two fundamental roles are as follows:  Participant design: Game theory is used to enhance the decision of a participant to get maximum utility.  Mechanism design: Inverse game theory designs a game for a group …

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Which is the best way to go for Game playing problem?

Heuristic approach is the best way to go for game playing problem, as it will use the technique based on intelligent guesswork. For example, Chess between humans and computers as it will use brute force computation, looking at hundreds of thousands of positions.

What is a Partial-Order Plan?

When a plan specifies all the actions you need to perform but specifies the order of the steps only when necessary, it’s called a partial-order plan.

What is Local Search Algorithms?

Basically, it’s Popular Search Algorithms. Also, a prospective solution. Further, moves to a neighboring solution. Moreover, returns a valid solution. a. Hill-Climbing Search Algorithm We can start this algorithm with an arbitrary solution to a problem. Also, it’s an iterative algorithm. Hence, the algorithm attempts to better solution by a single element of the solution. …

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What is a Chatbot?

A chatbot is Artificial intelligence software or agent that can simulate a conversation with humans or users using Natural language processing. The conversation can be achieved through an application, website, or messaging apps. These chatbots are also called as the digital assistants and can interact with humans in the form of text or through voice. …

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What is user Interface?

Generally, ES users and ES itself uses User interface as a medium of interaction between users. Also, the user of the ES need not be necessarily an expert in Artificial Intelligence. Although, at a particular recommendation, it explains how the ES has arrived. Hence, the explanation may appear in the following forms − Basically, the …

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What Brute-Force Search Strategies?

This strategy doesn’t require any domain-specific knowledge. Thus it’s so simple strategy. Hence, it works very smoothly and fine with a small number of possible states. Requirements for Brute Force Algorithms a. State description b. A set of valid operators c. Initial state d. Goal state description

What is AI?

is a field of computer science wherein the cognitive functions of the human brain are studied and replicated on a machine or a system. Artificial Intelligence today is widely used in various sectors of the economy including science and technology, healthcare, telecommunications, energy and so on. AI has three different levels: Narrow AI: AI is …

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What is a Depth-first Search Algorithm?

Depth-first search (DFS) is an algorithm that is based on LIFO (last-in, first-out). Since recursion is implemented with LIFO stack data structure, the nodes are in a different order than in BFS. The path is stored in each iteration from root to leaf nodes in a linear fashion with space requirement.

Explain applications of N.L.P?

a. Communication Basically, a computer is a medium to communicate with users. Also, to learn a new language we can’t force users. Although, for casual users, it’s most important. Such as Managers and children. As they don’t have time and inclination to learn new skills to learn new interaction skills. Basically, in natural language, it’s …

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What are iterative deepening depth-first search algorithms?

In iterative deepening DFS algorithms, the search process of level 1 and 2 takes place. It continues the exploration until it finds the solution. It generates nodes until it finds the goal node and saves the stack of nodes it had created.

What are the types of AI?

Artificial intelligence can be divided into different types on the basis of capabilities and functionalities. Based on Capabilities: Weak AI or Narrow AI: Weak AI is capable of performing some dedicated tasks with intelligence. Siri is an example of Weak AI. General AI: The intelligent machines that can perform any intellectual task with efficiency as …

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What are the types of Machine Learning?

Machine Learning can be mainly divided into three types: Supervised Learning: Supervised learning is a type of Machine learning in which the machine needs external supervision to learn from data. The supervised learning models are trained using the labeled dataset. Regression and Classification are the two main problems that can be solved with Supervised Machine …

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How to select the best hyperparameters in a tree-based model?

There are two best Hyperparameter in a tree-based model Measure the performance over training data Measure the performance over validation data We have to consider the validation result while comparing with the test results, so the answer is B

What are expert Systems Limitations?

Basically, we have noticed that no technology can offer an easy and complete solution. Also, large systems are too costly. Although, they require significant development time and computer resources. Also, ESs have their limitations which include − Limitations of the technology Difficult knowledge acquisition ES are difficult to maintain High development cost

What is the importance of N.L.P?

We can understand the advantage of natural language programming in an easy way as we consider two statements: “Cloud computing insurance should be part of every service level agreement” “A good S.L.A ensures an easier night’s sleep — even in the cloud.” Generally, if an individual is used to of NLP, in an entity, a …

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Explain a bidirectional search algorithm. What is it?

A bidirectional search algorithm runs two simultaneous searches. The first go forward from the initial state, and the second goes backward from the goal state. They both meet at a common point, and that’s when the search ends—the goal state links with the initial state in a reverse manner.

What is a Bayesian network, and why is it important in AI?

Bayesian networks are the graphical models that are used to show the probabilistic relationship between a set of variables. It is a directed cycle graph that contains multiple edges, and each edge represents a conditional dependency. Bayesian networks are probabilistic, because these networks are built from a probability distribution, and also use probability theory for …

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Explain the term “Q-Learning.”

Q-learning is a popular algorithm used in reinforcement learning. It is based on the Bellman equation. In this algorithm, the agent tries to learn the policies that can provide the best actions to perform for maximining the rewards under particular circumstances. The agent learns these optimal policies from past experiences. In Q-learning, the Q is …

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List down the techniques or algorithms mostly used in AI?

In general, there are certain algorithms that are mostly used, or we can say that they are the first one to approach to understand the complex scenarios. Here are some of them. Neural Network Generic Algorithms Reinforcement Learning

Explain in brief Artificial Intelligence?

According to the father of Artificial Intelligence, John McCarthy, it is “The science and engineering of making intelligent machines, especially intelligent computer programs”. Also, intelligence distinguish us from everything in the world. As it has the ability to understand, apply knowledge. Also, improve skills that played a significant role in our evolution. We can define …

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What is reinforcement learning?

Reinforcement learning is a type of machine learning. In this, an agent interacts with its environment by producing actions, and learn with the help of feedback. The feedback is given to the agent in the form of rewards, such as for each good action, he gets a positive reward, and for each bad action, he …

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Name some expert System Technology?

It includes: a. Expert System Development Environment Basically, hardware and tools are included in it. They are − Minicomputers, workstations, mainframes. LISt Programming (LISP) and PROgrammation en LOGique (PROLOG). Large databases. b. Tools Generally, tools are used to reduce the effort and cost. Powerful editors and debugging tools with multi-windows. They provide rapid prototyping. Have …

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What are the Different Types of AI?

Reactive Machines AI: Based on present actions, it is not capable of using previous experiences to form current decisions whilst simultaneously updating their memory. Limited Memory AI: This type of AI is used in self-driving cars – they detect the movement of vehicles around them constantly and add it to their memory. Theory of Mind …

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What is Ensemble Learning?

Ensemble learning is a computational technique in which classifiers or experts are strategically formed and combined. It is used to improve classification, prediction, and function approximation of any model.

What is Fuzzy Logic Implementation?

Basically, it can be implemented in systems with various sizes and capabilities. That should be range from mall micro-controllers to large. Also, it can be implemented in hardware, software, or a combination of both in artificial intelligence.

What is Hidden Markov Model (HMMs) is used?

Hidden Markov Models are a ubiquitous tool for modelling time series data or to model sequence behaviour. They are used in almost all current speech recognition systems.

What is Natural Language Processing?

We use English language to communicate between an intelligent system and N.L.P. Processing of Natural Language plays an important role in various systems. For Example: A robot, it is used to perform as per your instructions. The input and output of an N.L.P system can be − Speech Written Text

What are roles in AI career?

Software analysts and developers. Computer scientists and computer engineers. Algorithm specialists. Research scientists and engineering consultants. Mechanical engineers and maintenance technicians. Manufacturing and electrical engineers. Surgical technicians working with robotic tools. Military and aviation electricians working with flight simulators, drones, and armaments.

Explain the objective and related terminology used in the search algorithms of AI?

This is the most popular Artificial Intelligence Interview Questions asked in an interview. Searching is the universal techniques used in AI problem techniques. This algorithm is used to search a particular position. Every search terminology has some components. Problem space: this is the environment in which the search takes place. Problem Instance: it’s a result …

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What is the philosophy behind Artificial Intelligence?

As if we see the powers that are exploiting the power of computer system, the curiosity of human lead him to wonder, “Can a machine think and behave like humans do?” Thus, AI was started with the intention of creating similar intelligence in machines. Also, that we find and regard high in humans.

What are aspects of robotics?

Basically, robots have mechanical construction. That is to form or shape designed to accomplish a particular task. Also, it contains electrical components. That is a use of power and control the machinery. Basically, it contains some level of a computer program. Also, it determines what, when and how a robot does something.

What is Bidirectional Search Algorithm?

Basically, starts searches forward from an initial state and backward from goal state. As till both meets to identify a common state. Moreover, initial state path is concatenated with the goal state inverse path. Each search is done only up to half of the total path.

What is AI?

AI is a branch of computer science that stresses and finds a way of creating an intelligent machine that has the ability to work, think and reacts like humans.

Why Fuzzy Logic?

Generally, we use it for the practical as well as commercial purposes. Basically, we can use it to consumer products and control machines. Although, not give accurate reasoning, but acceptable reasoning. Also, this logic helps to deal with the uncertainty in engineering.

Which programming language is used for AI?

Below are the top five programming languages that are widely used for the development of Artificial Intelligence: Python Java Lisp R Prolog Among the above five languages, Python is the most used language for AI development due to its simplicity and availability of lots of libraries, such as Numpy, Pandas, etc.

What are components of N.L.P?

Basically, there are two components of Natural Language Processing systems: a. Natural Language Understanding (NLU) In this, we have to understand the basic tasks − Basically, the mapping to given input in natural language into useful representations. Analyzing different aspects of the language. b. Natural Language Generation (NLG) We have to produce meaningful phrases and …

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Explain Goal of Artificial Intelligence?

To Create Expert Systems it is the type of system in which the system exhibit intelligent behavior, and advice its users. b. To Implement Human Intelligence in Machines It is the way of creating the systems that understand, think, learn, and behave like humans.

What are benefits of Expert Systems?

a. Availability Due to mass production of software, expert systems are easily available. b. Less Production Cost As production cost of an expert system is reasonable. Thus, it makes them affordable. c. Speed Generally, expert systems offer great speed. Also, reduce the amount of work that an individual puts in. d. Less Error Rate Generally, …

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