Artificial Intelligence 2021

Iterative - Iterations in simple language is Practice. In real life when a student is preparing for an exam at that time if he/she needs a lot of practice, reading, following exercise questions, and providing our answers to understand the subject/ topic. Then n then only we get expertise in that particular concept or you can say area. And if you get more accuracy after practicing then you will get a high rank in that area right. Similar way we need to train our Machine Learning model so that they can be accurate at every time once we deploy them that's why this kind of learning is called  Iterative Learning . For this, we need to train our model with different kinds of data set so our model can learn first. The machine also needs to understand data, process it, and produce more accurate output. Most of the time Iterative Learning can be most accurate and faster. At the end of the day, iteration will result in an error-free return in investments. Figure. Iterative Learning Mach...

  Figure. Natural Language Processing Natural Language Processing (NLP) refers to the artificial intelligence (AI) method of communicating with intelligent systems using a natural language such as English. Processing of Natural Language is required when you want an intelligent system like a robot to perform as per your instructions, when you want to hear a decision from a dialogue based clinical expert system, etc. The field of NLP involves making computers perform useful tasks with the natural languages humans use. The input and output of an NLP system can be − Speech Written Text Components of NLP Figure. Components of NLP In this section, we will learn about the different components of NLP. There are two components of NLP. The components are described below − Natural Language Understanding (NLU) It involves the following tasks − Mapping the given input in natural language ...

Just like the Internet has changed the way we work & communicate with each other, by connecting us through the World Wide Web (internet), IoT also aims to take this connectivity to another level by connecting multiple devices at a time to the internet thereby facilitating man to machine and machine to machine interactions. Following  are four fundamental components of IoT system which explains how IoT works : 1.     Sensors/Devices:    First, various sensors and devices that are applied in the system help in the collection of very minute data from the surrounding environment. All of this collected data goes through the various degrees of complexities which may range from a simple temperature monitoring sensor or a complex full video feed. An IoT implemented system or device can have multiple sensors that are brought up together to perform functions more than sensing things. For example, our phone i...

As the Internet of Things continues to steer operations in the 21st century, numerous challenges are coming to light.  While the IoT still has the potential to transform business for owners, employees, and customers alike, those who already embrace this next-gen network still have some work to do. Not only are they trying to make the most of IoT integration to benefit their own company, but they’re also treading new ground and serving as role models for those who have yet to take the plunge.   There are many benefits to the increased adoption of IoT technology, says Kate Began, poly case sales and marketing manager, from the ability to monitor cargo anywhere to play your favorite music in the shower from a waterproof Bluetooth speaker. But there are still many challenges to widespread IoT adoption and to a secure, functioning global device network. From security challenges to the perils of high customer expectations, these five factors are big concerns for the growth and devel...

  Artificial Intelligence is definitely the future of the world. Artificial Intelligence will drive the economy of tomorrow. Are you excited about   Artificial Intelligence?   Google, Facebook, Apple, Microsoft are all moving ahead at great speed in improving this Artificial Intelligence. So, it’s very exciting! Software is going to solve that where it’ll look at the new information and present to you knowing about your interests what would be most valuable. So: making us more efficient. We’re focusing on autonomous systems and we sort of see it has the mother of all AI projects. Areas where Artificial Intelligence is going to impact our future lives. Autonomous Transportation:   As the companies like Uber, Google & General Motors are struggling hard to establish themselves at the top of this market, this would soon bring a complete change to an AI – guided transportation and would become a reality. All of the three from Uber to Google to General Motors all want ...

CRISP-DM stands for Cross Industry Standard Process for Data Mining. The CRISP-DM methodology is practical, flexible, and useful when solving business issues with analytics. The definition of CRISP-DM is a data mining technology or a methodology or a process that helps you or provides you a blueprint to conduct a data mining project. It was implemented in 1996 and was founded by major companies like Daimler Benz, ISL, NCR & OHRA. These companies have actually implemented in around 200 data mining users and tools and then they came up with this model. This is a non-proprietary documented and freely available process that’s what the actually designed, so everybody can use it. How does it help? CRISP – DM provides a roadmap, it gives you best practices and it provides you structures for better and faster results of using data mining, so that’s how it helps the business to follow while planning and carrying out a data mining project.   Business Understanding Business Understanding...

  We know humans learn from past experiences and machines follow instructions given by humans, but what if humans can train the machines to learn from the past data and do what humans can do act much faster, that’s called Machine Learning. For example, 1 method is the classification method. It can put data into various groups. The same classification method used to concede handwritten numbers and also be used to classify emails into spam and not-spam. It is the same method but it’s fed different training data and hence it comes up with different classification logic. Figure: Classification There are three types of Machine Learning Algorithms: Supervised Learning Unsupervised Learning Reinforcement Learning Supervised Learning: Here we have a teacher who gives us instructions i.e training data, which means here in supervised learning we have inputs also and outputs also and through that given data also known as labeled data we prepare a model and there we put our new I puts and...