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DexLab Analytics Presents Mega Artificial Intelligence Course In Python: An Online Demo

DexLab Analytics Presents Mega Artificial Intelligence Course In Python: An Online Demo

Dexlab Analytics is undoubtedly a leading name in the field of the Big Data Analytics industry. The latest offering from this institute is a course that is remarkable in so many ways. The course is Mega Artificial Intelligence Course In Python, which aims to cover everything you ever need to learn regarding artificial intelligence. To help you get a better grasp of the course we have also prepared an online demo and the demo video is attached at the end of the blog do check that out to clear away any confusion you might have.

Before getting into the course details, there are certain features of the course that we think you should know about. To begin with, you do not need any special educational background, you can hail from any stream and can still pursue the course because here we will teach you from scratch. Just having some mathematical knowledge is fine. We have kept things flexible here, so you can repeat the course if and when necessary. The notes that you will be needing for the course including the code sheets, will be provided to you in the beginning so that you do not have to waste precious time in class taking notes.

However, the nature of the course will be online, because due to COVID 19 situation offline classes are temporarily not possible. You will be given all the classroom videos, furthermore, there will be guidelines regarding Kaggle.com where we will teach you how to participate in this pioneering data science website, how to compete over there and offer you tips to increase your ranking. All in all the course aims to transform you into a super data scientist.

You can find the detailed course information, the online demo and brochure in the PPT format at

 

The course will be divide into three sections starting with PYTHON  PROGRAMMING for Data Science. Throughout the sessions, you will get familiar with the language, its libraries. You will be taught to use Plotly and handle projects before moving onto the second section which is AI( Artificial Intelligence) comprising three components namely Statistics, Machine Learning, and Deep Learning. Along with picking up the nuances, you would handle mega projects including one on self driving cars. Moving on to the next segment of Big Data get introduced to PySpark. Handling a growing amount of data could be tough, so, an introduction to Quantum Computing seems necessary before wrapping things up.

Do check out the course details in the video attached below that gives you a thorough tour of the entire course and also check out the course brochure. Our contact number is provided there along with our website address, feel free to contact us regarding any query.


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Retail Therapy Powered By AI

Retail Therapy Powered By AI

Retail has been one of those smart sectors that embraced the power of AI technology to offer a personalized shopping experience to the customers. Let’s have a look at how AI has been a great tool in helping the stores rake in money.

 Be it smart product recommendations by analyzing shopping patterns, or, offering better inventory management solutions today’s retailers are doing it just right. The sector needs to focus on training their employees, as undergoing customer market analysis courses is of paramount importance.

Offer personalized product recommendations

This has been one of the most revolutionary changes in the e-commerce industry. With AI-powered technology  retailers can offer personalized product recommendations to the customers. Using smart tools they can analyze the shopping preferences, shopping patterns of a customer as well as their browsing history.

The data provides them with valuable insight which they apply to recommend products following that specific customer need. By doing so, they can retain customers and experience a better conversion rate. Tools such as  Stitch Fix,  Boomtrain are carrying out this task successfully to recommend products that suit customer whimsies.

Smarter inventory management

Inventory management is one of the key areas the retailers have to focus on. Previously they would just stock up on items without having access to any valuable customer data. Now that they can sift through big data, they can analyze past trends and could predict what upcoming trends are to look out for. Being armed with data they now make decisions accordingly.

 In fact, to ensure that there is no gap in the supply chain robots are being put to use. Self-scanning robots used by Walmart could be a case in point here. These robots look for items that need restocking. Some stores are going one step further to use algorithms to analyze receipts to find out which products are in most demand and they restock accordingly.

Virtual assistants taking care of customers

Customers have no access to virtual assistants, chatbots who not only offers constant support but, also interacts with them offering personalized recommendations, as these bots are powered with NLP technology, they are more intuitive and capable of engaging with customers. In fact, with automation being available, sending a faster response to customer queries has also become more efficient. Navvi is a robot that handles customers along with handling other responsibilities.

Enabling shoppers to take immediate action

Any average person these days spends a good amount of time browsing through social media platforms, different sites which more often than not are used as advertising platforms. So, when a prospective customer finds something interesting, they check it out and then they go on to something else and later might forget about it.

But with AI-powered tools like Lens feature, they can capture the image of the product they like and search for it, thereby ensuring that they can embark on their shopping quest. This feature was initially introduced by Pinterest. With further application of deep learning for computer vision with python, there could be more developments in the field.

Taking chaos out of shopping with smart solutions

When buyers visit a store physically or, virtually they usually browse through scores of products to find what they need. Oftentimes they have difficulty locating the product they had selected online in the physical store. But, with a unique tool like Amazon Go, they can completely be at ease.

They can select the items and put in a virtual basket and when they enter the physical store they can easily track the items they had previously selected and that’s it. No complications involved and they enjoy seamless shopping experience. Zara takes a step further and deploys robots who fetch the product ordered and delivers it. 

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Identifying prospective leads

AI has introduced some exclusive features such as face recognition, which is being now utilized by retailers to target potential leads. This is leading to a seamless merger of experience one might get in a physical and virtual store. Face recognition feature is being used to find out which products customers are spending time on in the store and based on that, recommendations are being sent online.

The shoppers are no doubt having the time of their lives enjoying this digital shopping experience, they are now able to find and buy products they need instead of wasting money on something random. The retail sector is all set to take the next big leap with AI. Retail Analytics Courses are going to be in demand as the sector needs personnel who are proficient in data handling.

 


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Why Manufacturing Companies Should Implement AI?

Why Manufacturing Companies Should Implement AI?

Over the last couple of years we have witnessed an exponential growth in the AI domain. The expansion of AI along with its various subsets are being acknowledged and adopted by different sectors to garner benefits from its various applications.

The manufacturing companies are among those few smart decision makers who were quick to realize the deficiencies present in their current system, and how implementing AI technology could help them address those issues. Retail Analytics Courses are being designed to enable the future professionals to better handle the challenges of the sector.

The key challenges in manufacturing

Before we can proceed to discuss the ways AI is being incorporated in manufacturing, we need to have a thorough understanding of what are the key problem areas this sector faces on a regular basis to realize how AI can tackle those issues.

Operational efficiency, operational safety, inventory control, maintaining product quality, lower operational costs and demand forecasting are some of the issues the companies basically deal with.

Now have a look at how incorporating AI can benefit the companies and in which ways

Ensuring product quality

It is of utmost importance for any manufacturer to ensure that the products are absolutely flawless. So, the products undergo different stages of checking by trained and experienced professionals. But, despite so much precaution being taken faulty products do make their way into the market resulting in customer complaints and the company having to recall the product line. This could be a damaging factor for the brand.

However, with smart sensors in place, even tiniest of errors could easily be detected. Machine vision can scan the products when they are in the production stage and after spotting a problem sends alerts. Professionals having a background in computer vision course python, would be assets for this sector. Nokia’s machine learning based video application can be an excellent case in point as it allows to detect and rectify mistakes in real-time.

Achieving better maintenance standards

Asset failure is one of the key issues that bug manufacturers, due to untimely upkeep and lack of proper maintenance strategies, machines can breakdown often bringing the whole production process to a standstill mode.

Predictive analysis can solve this issue and ensure enhanced operational efficiency. It involves the application of analytics, sensors to keep the machines in check on a regular basis so as to detect any problem areas that need to be repaired or, replaced. This ensures that machine downtime does not impact the production process in any which ways and this also extends life span of machines. Roland Busch, Thales SA, are some of the companies that have successfully implemented and benefited from predictive maintenance technology.

Achieving efficiency in designing process

AI powered technology can definitely boost the designing procedure by taking the whole assumption factor out of the process. Predicting consumer behavior and deciding what products customers are looking for to come up with a design that matches that particular criterion is essential. A degree in customer marketing analysis training could enable a professional be proficient in this job.

Generative design software takes hassle out of the design process, it basically processes data regarding the criteria, different parameters, restrictions, time and budget constraints and offers solutions on the basis of that and also offers insight regarding which design might work best.

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Prioritizing security

Ensuring safety of the workers in any manufacturing unit is of utmost importance. Despite taking precautions and safety measures being in place accidents occur due to human error.

To minimize the risk factors AI powered industrial robots can be used in the plants and manufacturing units. The bots will process real-time data and analyze that to minimize risk in a hazardous work situation where human workers could be vulnerable. Since, these bots would be able to analyze data with precision there would be less room for errors.

Manufacturing companies are already applying AI techniques to ensure safe and efficient production environment. The hybrid workforce comprising human and robots , has already become a reality, in future more tasks could be allotted to robots to automate production process and reducing operational costs.

In order to retain jobs in the coming future one has to undergo specialized training such as deep learning for computer vision with python to land a job, because no matter how you look at it the future certainly belongs to AI.

 


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How Market Researchers Can Benefit from AI?

How Market Researchers Can Benefit from AI?

Market researchers usually have a hard time preparing and conducting surveys to gather valuable data on customers as well as competitors and sorting that data to offer actionable Intel to marketing heads to enable them to devise marketing strategies accordingly.

So, basically their job centers around data, data, and more data, it is solely reason enough for them to consider ditching their jaded and often erroneous data collecting system and step into the domain of AI by pursuing customer market analysis courses.

 How  Market Researchers View AI

Despite recognizing and appreciating the manifold advantages of AI, some uneasiness lingers in most industries regarding its applications and full integration.

However, market researchers were thankfully, quick to recognize the pros the AI package has to offer. The implementation of AI would take most of the hassle way from their job. Surveys conducted over the past couple of years show that almost 80% of market researchers are in favor of AI and they believe that it will be the harbinger of new opportunities. 

How AI Can Address the Woes of Market Researchers?

Any conversation with a seasoned market researcher would reveal the issues that continuously bug them. A huge amount of time and money that go into the process along with the enormity of data they have to process, can lead to frustration.

With rampant consumerism becoming a reality of modern society, the market researchers would need to deal with an even bigger amount of data.

Some agencies have already started migrating to AI solutions to address these concerns and they are seeing the difference already. Machine Learning Using Python is becoming a trend which they are veering towards.

Although companies are still holding back from fully integrating AI into their operations, in near future the scenario might change considering the benefits AI can offer

Shortening data processing time: Usually, it takes months to complete projects, but, with AI-powered tools, the duration of the projects can be shortened. Data processing and producing insight based upon data findings can be almost instantaneous.

 It would enable the marketing heads to tackle issues faster than ever before, thus gaining an edge over the competition. Report generation would take less time and the team can be employed to handle some other productive tasks.

Higher efficiency in data handling:  Any organization has to deal with a huge amount of data, as every year new data gets added to their database. However, when it comes to market research, mostly experience data is put to use while operational data which is mainly old data is shifted to the backburner. AI integration can solve this issue by combining both data sets, and combing through this massive data to produce insights and find new patterns in customer behavior which was earlier missed by your team.

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Improve survey quality:

Implementation of AI can take the errors out of the present survey system and make it more efficient. Using ML and NLP, survey questions can be shaped in a conversational style which would immediately put the respondents in a comfort zone thereby improving the chance of eliciting an accurate response. AI-powered tools can also put together a list of respondents who are apt for the survey and eliminating random ones out of the list.

Customize marketing strategy: As AI gets integrated into your market research process, it starts analyzing customer behavior by going through the bounce rate, as well as login data. As a result, it points out those customer, marketing teams need to work on. They get a chance to customize a marketing strategy for them.

There is no denying the fact that AI can transform the way market researchers work. Integration and adoption of AI would certainly take time but, eventually, the merger would happen. Since AI is a highly specialized domain, the market research teams need to upgrade themselves. Enrolling in a premier artificial intelligence certification in delhi ncr, would help them be prepared for a smarter future.

 


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How AI Can Be Applied in the Field of Special Education?

How AI Can Be Applied in the Field of Special Education?

The digitization of modern classrooms is an indicator of the fact that educators have decided to adopt tech to make learning a more rewarding experience for their students. In fact, some educators are making an effort to upgrade themselves with advanced courses like deep learning for computer vision with python.

But, not all children in a classroom can blend in with their classmates with ease, they have difficulty understanding teacher’s instructions or, even following what is written in the textbooks.

Yes, we are talking about children with disabilities, who cannot be taught in a typical classroom setting and who need special attention and today we are going to learn whether the transformative power of AI can make a difference in the lives of these differently-abled children.

How do we classify children who need special education

Children who have been detected with some form of physical, cognitive or learning disabilities such as ASD- Autism spectrum disorder, Dyslexia, hearing, or visual impairment, require a learning environment that is specifically designed for them.

What are the challenges they face in a traditional setting?

Usually, these children have problems coping with the traditional learning environment. They find it difficult to follow instructions, lessons, even their textbooks. They need personal attention from the teacher, and are unable to handle the pressure of competition.

What’s more, these children usually are subjected to bullying from other students, which can further discourage them. they need special tools, and lessons that are designed for them. These children also have a short attention span so, the reading material might not interest them.

How AI can be of help?

The introduction of AI in special education has opened up new avenues for both parents and teachers. Data Science training has enabled professionals to analyze student data to identify problem areas. There have been several studies on this and the findings are promising. With the application of AI-based methods, it is possible to help these children exercise more freedom as it allows them to learn at their own pace.

The Application of AI in special education is aimed to serve a dual purpose.

1) AI-based tools are used to detect disability

2) AI-based learning tools and methods are being adopted to aid learning

Now let’s take a brief look at how this dual application of AI is taking place and with what effect

1) AI-based tools are used to detect disability

Sometimes identifying a problem can lead you to the right solution. Usually, children who show apathy to learning or, are very slow to pick up lessons, treated as dumb. They are bullied and teachers keep complaining that they do not make an effort. But, what they fail to realize is that the child might have a learning disability.

But, now we have AI-enabled testing systems in place to detect children with learning disabilities.

 In the year 2008, a model was introduced to diagnose autism with the help of artificial neural networks technique. Even before this way back in 2003, a fuzzy cognitive map approach was taken to diagnose SLI or, speech-language impairment. Other systems involving artificial neural network techniques were developed to detect issues like dysgraphia, dyslexia. 

More data based research work on this is required. This would definitely create a demand for professionals who have undergone specialized training on neural network course python.

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2) AI-based learning tools and methods are being adopted to aid learning

 Children with special needs must have access to special learning tools that would make learning easier. There has been some considerable progress in this field.

  • Children with Autism have problems with both verbal and nonverbal communication. Developing social skills can be a challenge for them. To address this issue QTrobot was designed. This humanoid social robot is programmed to teach autistic children social skills. Other examples would be NAO robot, virtual assistant Siri which help children with ASD acquire more social skills.
  • ActiveMath employs Artificial Intelligence techniques to ensure children can have more freedom in selecting a convenient learning environment.
  • Spontaneous participation of the learner is essential for any learning process to be effective. If a child is having trouble concentrating then, he won’t learn anything. Smart Tutoring model was developed to evaluate the concentration level as well as the mood of the child, to develop a learning session that suits that particular child.
  • Widex’s Evoke is an intelligent hearing aid powered with AI technology which can help hearing-impaired children attend classes without any difficulty.

AI has the potential to transform the special education sector with advanced learning aids, specifically designed for differently-abled students. The field is expanding and it needs more research and collaboration among educators, app developers, engineers to come up with smarter solutions.

 


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Emerging AI Trends You Should Keep Track of

Emerging AI Trends You Should Keep Track of

AI is a dynamic field that is constantly evolving thanks to the continuous stream of research work being conducted. The field is being reshaped by emerging trends. In order to keep pace with this fast-moving technology, especially if you are pursuing Data Science training you should learn about the latest trends that are going to dominate this field.

Digital Data Forgetting

It is a curious trend to watch out for as instead of learning data, unlearning would take precedence. In machine learning data is fed to the system based on which it makes predictive analysis. However, thanks to the growing channels and activities the amount of data generated is increasing, and a significant portion of which might not even be required and which only contribute to creating noise.

Although it is possible to store the data utilizing cloud-based systems, the price an organization will have to bear for unnecessary data, does not justify the decision. Furthermore, it might also raise privacy risks in the future. The efficient handling of this data lineage issue requires systems that will forget unnecessary data so that it can proceed with what is important.

NLP

Now that chatbots are being put to use to provide better customer support, the significance of NLP or, natural language processing is only going to increase. NLP is all about analyzing and processing speech patterns. There is now a shift towards developing language models around the concepts of pre-training and fine-tuning and further research work is being conducted to make these systems even more efficient, however, the focus on transfer learning might lessen considering the financial and operational complications involved in the process.

Reinforcement Learning

 This is another trend to look out for, reinforcement learning is where a model or system learning involves a preset goal and is met with reward or, punishment depending upon the outcome. This particular trend might push AI to a whole new level. In RL, the learning activity is somewhat random and the system has to rely on the experience it has gained and continues to learn by repeating what it has learned, and as it starts recognizing rewards it continues working towards it until the learning takes a logical turn.  Research works are being conducted to make this process more sophisticated.

 Automated Machine Learning

 If you are aware of Google AutoML, then you already have an inkling of what AutoML is. It basically focuses on the end-to-end process and automates it. It applies a number of techniques including RL, to reach a higher level of accuracy. It works on raw data and processes it to suggest a solution that is most appropriate. It basically is a lifesaver for those who are not familiar with ML. However, there are programs available that enable professionals pursue Machine Learning Using Python who are looking to gain expertise in this field.

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Internet of Things

IOT devices are a rage and they are able to collect a huge amount of user data that needs to be processed to gather valuable information. However, there could be certain challenges involved in the data collection process which lead to error. The application of ML in this particular field can not only lend more efficiency to the way IOT operates but it can also process a large amount of data to offer actionable insight. The information filtered this way could help develop efficient models for businesses and various other sectors. The merger of IOT and ML is definitely a trend that is definitely going to be revolutionary.

AI technology is getting more sophisticated with emerging trends. The manifold application of AI is opening up new career avenues. Enrolling in a premier artificial intelligence training institute in Gurgaon, would be a good career move for anybody looking forward to having a career in this domain.

 


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How AI is Changing The Way You Conduct Business?

How AI is Changing The Way You Conduct Business?

In the pages of sci-fi, we find a world that is completely driven by AI, but, we no longer have to wish for a dystopian world to become a reality to experience AI firsthand. Our world as we know it is gradually being reshaped by the powerful presence of AI. From your Smartphone to virtual assistants, AI is taking slow but firm strides which is evident from the high demand for courses like artificial intelligence certification in delhi ncr.

So, when everything is being impacted by AI, why should your business lag behind? You would be surprised to learn the incredible changes AI could bring to the table.

Be it managing administrative tasks or, ensuring data security, AI could streamline operations and add efficiency to every task that needs to be performed to ensure zero error. Here is how you can make the difference
 

  • Implement AI to smoothen your HR practices: Managing your employees and recruiting new ones are essential tasks for any organization. Your HR department can be more efficient with their tasks at hand with the help of machine learning. Dealing with scores of applications while recruiting new faces can be a mundane task. But, now processing applications and sorting out the ones that match the criterion gets easier and so does the entire hiring process. Throw in chatbots in the interview process to ensure that you select the right candidates.
  • Lessen errors during manufacturing: During the manufacturing process, oftentimes  one or, two faulty products end up spoiling the image of the brand and most importantly you end up spending time, money, and personnel for return and refund procedure. To err is human but, with AI coming into play, any kind of glitch could easily be detected and prevented at an early stage. This would ensure that only quality products are ending up in the showrooms.
  • Customize marketing strategies: It is so hard to guess what your customers want and even more difficult to chalk out a marketing plan around that guesswork. However, advanced analytics could help you keep a track of consumer behavior because it is purely based on data. So, now that you have eliminated the guesswork, you can come up with a marketing strategy that actually works to entice customers.
  • Provide customer service round the clock: While running your business you must have noticed how difficult and essential it is to stay in touch with constant queries. People who are buying from you might have umpteen number of queries and you need a big team to handle that. However, despite your best efforts, some queries go unanswered, this might create a negative impact on the customers. So, why not take the help of chatbots who can handle all the primary queries round the clock and provide customer satisfaction? Critical queries could be handed over to a support team with specialized knowledge.

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You can do more with AI-powered tools and systems to make your business grow. The world is moving with AI towards a brighter future and, it is time for you to welcome and embrace its power.

 


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AI’s Contribution to Photography: An Assessment

AI’s Contribution to Photography: An Assessment

The next time you are buying a smart phone or a digital camera, instead of concentrating on the lens specifications, try to find out what the manufacturer has to say about artificial intelligence. Because the nature of photography has changed for good in a world fast recalibrating to keep pace with the exigencies of advanced computing. In this article we will examine how artificial intelligence has transformed the way the world looks at photography now.

Smart Devices

Photography, the idea of sharing with others what we can see through a lens, has been a long developed art with teachers and mentors passing down acquired skills to protégés and juniors for years now. However, with the advancement of AI’s uses in the photography industry, things have changed tremendously.

Take for instance Apple’s A11 Bionic neural engine chip that powers the latest generation of iPhones. The chip is fitted with AI technology that assists in image and face recognition, AR applications and more. Google Pixel then came out with its high-tech hardware chip designed for dedicated image enhancement and image processing.

The Chinese smartphone, Huawei’s P20 Pro, features four cameras. Besides achieving the highest DxO Mark score to date, the Huawei P20 Pro is packed with AI features, such as real-time image scene recognition, meaning it can discern 500 scenarios in 19 categories, such as animals, landscapes, as well as an advanced night mode, where the AI assists in processing noisy photos, making them almost perfect, says a report.

So it has become the norm for smart devices to have inbuilt AI powered hardware that help enhance the process of photography unlike traditional cameras. Manufacturers are concentrating on image capture and real-time processing because it is a market differentiator.

Processing professional photographs

Professional photography needs to be processed and cannot be used in the RAW format. But the procedure has been enhanced by AI technology lately. For instance, recently, PetaPixel released a research paper that talked about how extremely underexposed images can be retrieved through techniques wherein AI is applied to the digital images. This technology can be used in high-end security cameras as well.

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Photo optimization

Photo optimisation is what AI has been able to take to the next level. A team of AI developers at Skylum is working on technology that will allow smartphone images to be expanded and printed with very high resolution and sharpness. This technology will help consumers lagging behind with older smart phones and old technology to optimise photos taken years ago. Other companies are trying to build technology that will compress RAW images up to 10 times the original heavy files without loss of data. 

It might seem like AI is intruding into the art space of photography, especially for professionals who have spent years honing the art of taking and editing photographs. But for the common user, AI powered technology is a boon and this technology is being sought by the best tech companies across the world. In India, artificial intelligence certifications in Delhi NCR are springing up to cater to a growing clientele that wants to join the AI revolution.

 


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5 Crucial Subsets of Artificial Intelligence

5 Crucial Subsets of Artificial Intelligence

As simply as can be said, artificial intelligence is a machine’s ability to replicate human intelligence and accept new inputs and perform tasks on them like human beings, learning from experience. The term was coined in the 1950s but it has today come to significantly become popular in relation to large data sets and new advanced algorithms.

AI has become the most revolutionary advancement in computing science and it is powering all sectors of the economy from banking to healthcare and agriculture today. There are many sciences branching out of artificial intelligence like machine learning, deep learning, neural networks, computer vision and robotics. Let us learn a little about each of these.

Machine Learning

Machine Learning, a crucial subset of artificial intelligence, is the machine’s ability to learn from experience with no need for human intervention explicitly. It is the most widely used form of AI in the market today. Machine Learning refers to the computer programs that are fed data, learn from them and use this experience to take intelligent decisions. Machine Learning is used in analysis, fraud detection and GPS based predictions to name a few. 

Neural Networks

Neural networks are a bunch of algorithms modelled after the neural networks that make up the human brain. They are designed to absorb and assimilate and interpret sensory data through labelling or clustering row input. The patterns they sense and interpret are in the form of numerical data, a format all text, images or even sounds must be translated into for a computer to understand. They help label, cluster and classify data based on similarities in the input fed.

Deep Learning

Deep Learning is a technique of machine learning that uses neural networks to learn up the way humans do – by example. And it does them accurately. It is the science behind driverless cars that can distinguish a lamppost from a person. Deep learning requires a large amount of labelled data sets to be able to work and effective and substantial computing power. Deep Learning finds its applications in aerospace technology, healthcare and driverless locomotives industry among others.

Robotics

A robot is a machine capable of sensing and interpreting and interacting with its environment. Robots have become much smarter and intuitive, thanks to artificial intelligence. Robotics is an interdisciplinary field of science and engineering that is powered by a consolidated science of mechanical engineering, electrical engineering, computer science, and algorithms. Robots are used in automobile manufacturing and used to move objects in space or related fields.

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Computer Vision

Computer Vision is the field of study that seeks to enable computers to “see” virtually like the human eyes do. A computer learns by labelling or classifying various objects, albeit much faster than human beings. Its goal is image classification and recognition. The Internet is inundated with pictures and photographs. In order to search for these images, the computer system needs to know what is in them. This is where the technology of computer visions comes in.

So you see how vast the scope of artificial intelligence really is. It is a science unto itself. To learn more about the science, professionals are increasingly joining artificial intelligence training institutes across the world. DexLab Analytics, the institute that brought this article to you, is a premiere artificial intelligence training institute in Gurgaon.

 


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