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artificial intelligence and machine learning

AI AND MACHINE LEARNING

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artificial intelligence and machine learning

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  1. ARTIFICIAL INTELLIGENCE(AI) AND MACHINE LEARNING Artificial intelligence (AI) and machine learning (ML) are the most trending fields nowadays, machine l earning helps machine to learn with the help of data provided and can only do specific task. In AI system is intelligent and can input multiple data. Just check it out: We have another blog related to artificial intelligence in real business world. Relationship between Artificial intelligence and Machine Learning : Machine learning is used in AI. ML is a method through which we can feed a lot of data to a machine so that it can make its own decision. AI is a vast field, in AI we have ML, NLP, image recognition, deep learning etc. In AI, you try to make machines behave like human beings.

  2. Which is better, AI or ML ? AI makes machine to think and behave like human while ML provide data to the machine for accurate output. ML comes under AI, Both AI and ML are best in doing their work efficiently. ARTIFICIAL INTELLIGENCE AI makes machine seem they have human intelligence, as it is a broad area of computer science. The term AI was first coined back in 1956 by Dartmouth professor John McCarthy. He called a group of scientist and mathematicians to see if a machine could learn like a child does. What is the history of AI ? Artificial intelligence was first termed in 1956 at Dartmouth College. First Turing test was taken in 1950. In 1957, the first chess program was written by Alex Bernstein. Unimate was the first robot used in the 1960s. The first chess playing computer (Deep blue) defeated the world chess champion in 1997. • • • • • What are domains of AI ? Deep learning • Igor Eisenberg in 2000 coined the term deep learning while there was a discussion of artificial neural networks. Deep learning algorithms are inspired by function and structure of human brain, it is a subfield of machine learning that uses complex algorithms to train a model. Machine learning • ML is an application of AI that allows a system to automatically learn and improve from experience. ML is mainly concerned with accuracy and patterns, deals with structured and semi-structured data.

  3. Computer vision • Computer vision helps computer learn and understand images and videos using digital images from cameras and videos and deep learning models, machine can accurately identify and classify objects. Image processing • Image processing is a method to perform some operations on an image, in order to get an enhanced image or to extract some useful information from it. Natural language processing (NLP) • NLP is a branch of AI that gives a machine the ability to read, understand and derive meaning from human language. NLP refers to the artificial intelligence method of communicating with an intelligent system using natural language. What are types of AI ? There are three stages of AI : Artificial narrow intelligence (weak AI) • Artificial narrow intelligence, also known as weak AI, can only perform tasks that are assigned to it. Currently are on the level of narrow intelligence. Alexa is the best example of narrow intelligence. Artificial general intelligence (general ARTIFICIAL INTELLIGENCE) • Artificial general intelligence is a strong AI, machines that can perform any task that a human can. Machines have strong processing units, but they are not capable of thinking like human beings. Artificial superintelligence (strong Artificial Intelligence) •

  4. Artificial superintelligence is a term used for when machines will surpass human intelligence and can perform tasks that any human being can not. This is yet fictional and can only be seen in movies and books. Application of ARTIFICIAL INTELLIGENCE ? Banks use AI to organize operation, invest in stocks etc. AI has been applies to video games, like bots designed to stand in opponent where human aren't available. •Medical clinic use AI to organize bed schedule, make staff rotation, provide medical information etc. •Customer support using chatbots, Siri, humanoid robot etc. • • HOW ARTIFICIAL INTELLIGENCE IS USED IN REAL BUSINESSES Artificial intelligence(AI) approaches and concept less than a decade. AI is the branch of computer science that aims to answer turnings question affirmative. It is the endeavor to simulate human intelligence in machines. When people think AI, they often think big such as curing cancer or solving climatic change everybody is dreaming up the biggest problem possible and attempting to solve them with AI. JUST 20% of surveyed executives use AI related technologies in their business. With the right business case and the right data, AI can deliver powerful time & cost savings as well as valuable insights you can use to improve your business. For more information regarding this topic check out our previous blog artificial intelligence in real; business world MACHINE LEARNING Machine learning is a branch of AI. ML was termed by Arthur Samuel in 1959. ML helps machine to learn automatically it does not need to be programmed regularly. ML allows machine to learn from data so that they can give accurate output. Types of machine learning Supervised learning •

  5. In this learning machine works under the supervision. It provides output with the help of labeled data. If I show you an image of a dog and tell you it's a dog it is labeled data. It has feedback mechanism. Unsupervised learning • In this machine have to work on data which is not labeled, machine identifies pattern and try to give response accordingly. Feedback mechanism is not there. Reinforcement learning • It uses agent and environment observation action reward. It is a machine training method based on rewarding desired behavior or punishing undesired ones. In general, a reinforcement learning agent is able to perceive and interpret its environment, take actions and learn through trial and error. Why is Machine Learning is important ? Increase in data • Tons of data is produced daily, ML is used to organize that data efficiently. Solve complex problems • ML can solve complex mathematical problems easily with the help of mathematical algorithms. •Improves decision-making Helps make faster and accurate decision based on data sheets provided. Algorithms of Machine learning:- Linear regression linear regression is a linear modelling approach to find the relationship between one or more independent variables (predictors) denoted as X and dependent variable (target) denoted as Y. Logistic regression Logistic regression is used for a different class of problems, known as classification problems. It measures the relationship between a dependent variable and one or more independent variables using a logistic function.

  6. Decision tree It is a tree shaped diagram used to determine a course of action. Each branch of tree represents a possible decision, occurrence or reaction. Math in ML ? Mathematics used in machine learning are statistics, probability, calculus, linear algebra and mathematical algorithms. Application of ML ? 1.Image recognition 2.automatic language translator 3.virtual personal assistant 4.product recommendation 5.Email spam and malware filtering

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