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Tag: Machine Learning Online Training

Steps to create a dashboard in Tableau

Posted on by Imarticus Learning

If you are having trouble with the excel sheets and finding it hard to create complex formulas to deal with the data, the Data Visualisation tools such as Tableau are here for the rescue! It can help use unmanageable data into beautifully crafted interactive dashboards. Those who have Tableau certification are hot properties in the Data Analysis and Data Science fields. 

Tableau is easy to use, works faster, and is also easy to set up. The tool is available in both paid and free versions. Knowing how to operate this will be an added advantage while doing any Artificial Intelligence and Machine Learning course. 

Getting this software and creating a dashboard is required to get a simplified version of the raw data that you are dealing with. SO, here are the steps to create a dashboard in tableau. 

Step #1 Creating a dashboard

Download and install the Tableau software to start the process. Once it is set up, open it and click on the ‘New Dashboard’ button to create a fresh one. Give an appropriate name to this dashboard so that it is easy to identify.

Step #2 Adding sheets to the board

The next step is to bring in the excel sheets with the data that you need to work on. Drag the required sheet onto the dashboard space. Alternatively, you can also select the most relevant data from a sheet, instead of the whole sheet. 

Step #3 Add additional sheet(s)

Tableau dashboard allows adding as many sheets as required for the data analysis. The additional sheets may be added in the relevant space and can process the data on all or selected sheets, as required.  

Step #4 Customization

The next step is where you customize or filter the data as per the requirement to create an interactive dashboard. Choosing layouts, adding images or texts, navigation to move from one data to another set, etc can be done at this stage. 

Step #5 View and share the data

Once all the customization is complete, view the data in full-screen mode and see if any changes are needed. Once satisfied, you can share the dashboard with others for review and discussion. 

Why is Tableau important?

Tableau is a data simplifying tool that helps manage a vast data resource. It can easily blend with AI to make faster and smarter decisions regarding the data. It also assists in integrating the data to work directly with various models of Machine Learning. Having a Tableau certification will be an asset, especially one pursuing an IIT Artificial Intelligence course or an Artificial Intelligence and Machine Learning course. Integrating the results of data interpretation decisions made using AI and ML into visualized data using Tableau helps people understand it better. 

best artificial intelligence courses by E&ICT Academy, IIT GuwahatiTableau opens a way for qualifying and quantifying the data while also identifying any particular pattern with the missing data. It is one of the robust tools that is required while implementing the machine learning models or solutions so that the business side can also understand and visualize the analysis or predictions. 

Conclusion

While the top-rated Artificial Intelligence course by E&ICT Academy, IIT Guwahati can develop a qualified and faster data analyst, the Tableau tool helps them be smarter. The drag and drop spaces on the Tableau dashboard allow you to investigate and relate the data with the intended outcome. It can work with multiple external data resources, not just the excel sheets. In other words, a single dashboard can combine data from various sources. Here, the visualization is possible with the help of charts, graphs, maps, tables, and some advanced methods.   

best Artificial Intelligence courses by E&ICT Academy, IIT Guwahati

How digitization through artificial intelligence and machine learning technologies has gained momentum post COVID-19?

Posted on by Imarticus Learning

In just a few months, the COVID-19 pandemic has managed to do what normal times would have taken years to achieve – a paradigm shift in the way companies in every industry and sector do business. Artificial intelligence and machine learning have been at the forefront during these challenging times. 

As the world gradually finds its way back to usual ways of life, it is interesting to see how the global crisis has paved the way for behavioral shifts, learning, and innovation. 

AI and ML in the Post-Covid-19 World

With the acceleration of digitization through Artificial Intelligence (AI) and Machine Learning (ML), digital sales have seen a boost, and businesses have focused their tech investments on cloud-based products and services. From online grocery stores and EdTech sites to online pharmacies and OTT players, the post-COVID-19 world looks very different through the AI and ML lens.

So, here are some examples to show how AI and ML technologies have gained momentum post-COVID-19:

  • AI and ML have been impacting the healthcare industry since long before the pandemic hit. AI algorithms have and continue to help in quickly sifting through large datasets to help identify similar diseases and their possible cures to accelerate the COVID-19 research work. 
  • AI and automation technology have also eased the healthcare sector’s administrative load by automating various processes. For example, data processing algorithms to extract data from internal systems and automatically generate medical reports and necessary audit trails have gained momentum post-pandemic. 
  • Also, advancements in ML will continue to help create new revenue streams. For example, scientists, drug researchers, and pharma companies are increasingly turning to AI and ML data processing algorithms to facilitate vaccine and drug discovery and their possible impacts on people. 
  • Lockdowns and social distancing norms have boosted online markets and the digital economy. However, even when the pandemic is gradually ebbing, customers are expected to continue using doorstep services as they did during the peak crisis. Hence, technologies like Augmented Reality (AR) and Virtual Reality (VR) have increased among eCommerce platforms to deliver a better customer experience. 
  • Talking about customer experience, the online retail industry has ramped up its use of AI chatbots and smart assistants to attend to the ever-increasing numbers of digital customers. Hence, the use of AI has helped streamline digital services, online ordering, and delivery systems. 
  • The pandemic has given rise to a digital workforce. To this end, the use of AI to quickly process applications, scan for eligibility and qualifications and perform other mandatory hiring checks has become the norm and is only expected to increase in the near future. 
  • The financial sector has also seen a dramatic rise in the use of AI and automation to serve its customers better and quicker during challenging times. For instance, banks leverage AI to help customers safely upload documents, categorize them and expedite processes without any delay. 
  • Lastly, greater digitization has also increased the risks of cybersecurity threats during the pandemic. While conventional cybersecurity risk management systems have failed to keep up with evolving cyber threats, AI offers innovative defenses. The pandemic has only nudged organizations to adopt holistic approaches to cybersecurity through AI and ML and create an integrated security system. 

How to Find the Best Artificial Intelligence Course?

If you want to learn AI and get a certification in AI and ML, opting for an online course can be the best call. But before you sign up for the course, ensure that it offers hands-on experience with real-world projects and has a curriculum with extensive coverage of concepts related to machine learning, NLP, deep learning, data science, and computer vision. 

With rampant use of artificial intelligence and machine learning, how are financial institutions dealiing with problems related to data bias and transparency?

Posted on by Imarticus Learning

The public and private sectors are increasingly turning to machine learning (ML) algorithms and artificial intelligence (AI) systems to automate every decision-making process, and financial institutions are no exception.

In addition to widespread use in the capital markets, artificial intelligence and machine learning are used in financial services to make insurance decisions, monitor user behavior, recruitments, fraud detection, credit referencing, and underwriting loans.

However, while AI and ML have brought innumerable benefits to financial institutions, they also have their share of woes in the form of data biases and transparency issues. The question is, how are financial institutions dealing with these problems?

Bias and Transparency in the AI Context

AI systems are powered by algorithms that “train” by reviewing massive datasets to ultimately identify patterns and make decisions based on the observations. Hence, these systems are no better than the fed data, resulting in unconscious data biases.

On the contrary, transparency in the context of AI refers to the ability to explain AI-based decisions. Given the increasingly complex findings and algorithms, ensuring transparency to different stakeholders is vital in the financial sector, both from compliance and business value perspectives.

Biases can occur in many ways. For example, bias due to incomplete data occurs when the AI system has been trained on data that is not representative of the population.

Likewise, the dataset could be biased towards previous decision-making processes, the programmer may introduce their own bias into codes, or business policies pertaining to AI decisions could be biased themselves. The bias of any form eventually leads to unfairness and inequities in financial services.

Dealing With AI Bias and Transparency

Although the use of AI and ML give rise to data bias and transparency issues, they have become indispensable for the functioning of financial services. So, the only course of action left to financial institutions is to adopt ways to get around the problems. Some of them are listed below:

  • Financial institutions and firms can have appropriate controls and monitoring tools to ensure that new data entering the pool is reliable and of high quality. 
  • In addition, some organizations have developed tools to determine if a potential AI solution is biased. 
  • When building AI systems, it is wise to gather a team with domain expertise, model development skills, data engineering capabilities, and commercial expertise. 
  • Organizations can undertake impact assessments of the AI solutions to ensure they are transparent and explainable, as well as determine how the AI-based decision-making process will impact customers. 
  • When engaging with AI technologies, financial services can apply safeguards to ensure that business outcomes are achieved, and customers’ interests are protected. 
  • Another way to minimize data biases is to be open on the user data, match and align data with the target segment, and set up review cycles with legal and statistical experts. 
  • Tracking mechanisms that allow one to track the decision-making mechanism of algorithms can be put in place to eliminate bias and ensure transparency as much as possible. 
  • Lastly, it is pertinent for institutions to document their approach to handling bias and review it after every stage of development and use of the algorithm.

What to Look for in an Artificial Intelligence Course?

If you want to learn AI and ML, there are several online courses you can choose from. An AI and ML certification course that makes you future-ready will have a robust curriculum covering critical concepts related to data science, machine learning, NLP, deep learning, and computer vision.

In addition, the program should offer in-depth experiential learning through hands-on involvement with real-world projects.

Why artificial intelligence and machine learning is the new blue print for the data science industry

Posted on by Imarticus Learning

Data science is a broad discipline concerning data systems and processes with the aim to maintain data sets and derive insights from them. On the other hand, Artificial Intelligence (AI) pertains to mathematical algorithms that can replicate human thought processes to understand complex relationships, plan for the future and make actionable decisions.

Machine Learning (ML), on the contrary, helps to implement AI by “training” computers to solve various tasks. Data science incorporates several areas of artificial intelligence and machine learning while primarily focusing on gaining insights from data.

But, how are these three fields related, and what is the impact of AI and ML in shaping the data science industry? Let’s find out.

Data Science, AI, and ML: Where Lies the Difference? 

Data science finds widespread use in several businesses to improve production processes, innovation of product design, and enable strategic planning. It involves techniques of mathematics, statistics, computer science, and even ML to extract knowledge from data and provide insights and decision paths. 

On the contrary, AI enables computers to observe their environment and make decisions based on what they observe. Some of the most widespread uses of AI include processing clinical data, creating chatbots and smart assistants, and financial planning. Add the machine learning component, and AI can enable computers to solve new problems such as classification and predictions.

The fields of data science, AI and ML overlap significantly and yet have subtle differences. In a nutshell, data science gives insights, AI produces actions, and ML facilitates predictions.

The Combined Effect of AI and ML on Data Science

Data science and data analytics have long been revolutionizing the business landscape. Companies that have mastered their use of data science and analytics aim to delve deeper into data to increase efficiency, boost their bottom lines and gain a competitive edge.

Thus, they are looking to incorporate AI and ML into their data infrastructure to achieve business goals. For instance, call centers have long been using conversation analytics software, platforms that leverage AI and ML to gain better data insights. 

Following are a few more examples to show how AI and ML combined with data science make a remarkable difference to organizations:

  • Conversational AI systems such as chatbots and smart assistants engage in highly interactive conversations with customers and users and capture actionable user insights in the process. 
  • Predictive analytics applications enable the analysis of dynamic datasets to make financial predictions, forecast business trends, customer behavior, etc. 
  • Hyper-personalization systems enable customized offerings to customers, such as product recommendations, targeted advertising, personalized medical care, and financial planning. 
  • Also, organizations can consistently respond to evolving threats, thanks to anomaly detection systems that leverage the potential of adaptive fraud detection and cybersecurity processes.

The business value of data science alone cannot be understated. However, integrating it with the tools and techniques of AI and ML has way more potential to produce actionable insights from the ever-expanding data pool. In conclusion, AI and ML have been impacting the data science industry for a long time and will continue to do so in the foreseeable future with even more ground-breaking innovations.

How to Learn AI?

Looking for an artificial intelligence course? There are several AI and ML courses available online with extensive coverage of data science, ML, NLP, deep learning, and computer vision. But before you settle on a course, ensure that the curriculum offers practical learning through real-world projects, has scope for ample industry exposure, and provides a globally recognized certification after course completion.

How Providers Can Use AI to Improve the Payment Integrity Process

Posted on by Imarticus Learning

Nowadays AI is utilized successfully and has proven to be an efficient, cost-effective, and reliable solution to cut down inappropriate payment claims worth a million dollars every year. The anomalies and patterns can be detected in less than a minute which helps to decrease fraud, system abuse, and future wastes.

From the provider’s point of view, they can be educated well to ensure evidence-based and high-quality alternatives. Learn more to know how the AIML program by Imarticus uses AI to improve the payment integrity process.

AI and Payment Integrity

A huge data volume from the providers, facilities, labs, etc. is integrated with AI-based computer power systems. This recognizes patterns in the data in a very effective and automatic way and helps to identify false claims. However, the billing behavior of the providers is difficult to detect as they are usually dealing directly with third-party enterprises for handling billing and coding issues.

This outsourcing may result in missing clarity and inconsistent processes which can ultimately lead to upcoding errors and fraudulent claims.

Thanks to the AI certification course, the identification of errors and fraud is a quick procedure with high precision and accuracy and the errors can be avoided drastically.

artificial intelligence and machine learning coursesInteroperability, APIs, and NLP Efficiency

The real innovation lies in the fact that the medical records of the patients can be directly obtained from the providers of EHRs with firm signed contracts.

This kind of interoperability helps in making the tasks work automatically like pre-authorization of the requests as per the need. This saves the manual working hours and makes the entire system run fluidly.

AI-based natural language processing (NLP) can further accelerate the time-saving process by around 40 percent when used on unfiltered data in the review stages. This helps in the augmentation of the staff efficiency and reduction of the costly human resources like nurses.

Integrating technologies like AI, NLP, robotic processing, and machine learning courses can give the payers the advantage of controlling the expenditure. Furthermore, it gives a helping hand to the providers to better manage the revenue systems to have a more unified and fluid cash flow within the system.

Prepayment cost avoidance model

One of the emerging trends of the industry is a significant shift to a prepayment from a post-payment cost avoidance model. It results in cost reduction related to reprocessing, reworking, and claim recoveries. But, the payers have to be super cautious when adopting this method as it is not yet well demonstrated and proven. Payment integrity based on AI is positioned very uniquely and this prepayment cost reduction model is close to becoming a reality in the industry soon.

Educating the providers

To overcome overutilization and fraud claims another approach that can be employed is their pre-detection by the providers themselves even before the claim submission. During the overpayment or appeal recovery process, the providers can be educated about the non-compliance, errors, overpayment issues, or the reasons for service rejection. This can increase the cooperation from the providers and helps decrease the number of appeals made.

On the same lines, AI-based technologies can analyze the data sets and send responses to the doctors, and list all the factors causing the denial of the claim and also about the unnecessary medical care as mentioned in the health plans.

Conclusion

Finally, analytics and solutions based on AI can ensure to cut down inappropriate claims significantly by identifying the wrong claims and acting upon them. Learn AI and improve the healthcare systems by making proper and efficient use of AI-based algorithms and methods.

How Artificial Intelligence and Machine Learning Is Altering the Marketing Landscape?

Posted on by Imarticus Learning

In this technological era, new technologies are being introduced in the market now and then. Businesses are no more using the traditional marketing methods to generate ROI (Return on Investment). Businesses are using new-age technologies like AI (Artificial Intelligence) and ML (Machine Learning) for better marketing and promotion.

Many young marketers are looking for a certification in AI & ML for securing better job roles in the marketing industry. The marketing landscape is continuously changing, and businesses need a sustainable solution. Read on to know how AI & ML are disrupting the traditional marketing landscape.

Use cases of AI and ML in marketing 

 One can see many real-life use cases of AI and ML in marketing around them. Some of the most popular use cases of AI & ML in marketing are listed below:

  • Businesses now use chatbots for their websites or software applications. Chatbots can interact with customers all day long and can solve basic queries. With a better user experience, businesses can retain their customers.
  • AI & ML can help provide accurate information to customers whenever needed. Inducing automation in marketing processes can reduce the manual load on an organization.
  • AI and ML tools are used by businesses to track dark social sharing up to an extent.
  • Many businesses are planning to use self-driving vehicles for marketing campaigns.

Driving factors for the use of AI & ML in marketing

 At present, businesses need to create personalized marketing content based on the preferences of the customer. Predictive analysis powers of AI/ML tools are helping businesses to create personalized marketing content. The recent COVID pandemic made it difficult for marketers to connect with their customers.

There was no physical interaction with the customers during the pandemic. AI & ML can help in collecting customer data even without stepping into physical markets. The need to decrease human labor in marketing processes has also forced businesses to go with AI and ML tools. With automated marketing processes, businesses can cut costs and boost ROI. In recent times, many businesses have focused on hiring marketers that have a certification in AI & ML for better results.

 How AI & ML are altering the marketing landscape 

Traditional marketing campaigns are launched with minimal insights. With AI & ML, you will have better insights before launching marketing campaigns. Marketing campaigns are becoming target-specific with AI & ML.

An ML/artificial intelligence course can help in learning more about disruptions caused in the marketing landscape. Businesses have to adapt according to the ever-changing marketing landscape to retain their market share. The benefits of AI & ML in marketing are listed below:

  • Marketers are getting better sales leads with AI & ML tools.
  • Marketers can understand the customer behavior and then launch marketing campaigns accordingly. It is better to understand the pain points of customers and then create personalized products/services.
  • Businesses are leveraging the power of customer data with AI/ML tools. The overall marketing cost is also decreased with the use of AI and ML.

How to learn AI & ML in 2021?

Young aspirants can go for the ML/artificial intelligence course offered by Imarticus Learning. The course name is ‘Certification in Artificial Intelligence & Machine Learning’ sponsored by E&ICT  Academy, IIT Guwahati. The certification in machine learning and AI follows an industry-approved curriculum. With numerous real-life industry projects and assignments, Imarticus offers a better learning experience.

Conclusion

Online certification in machine learning and AI can help marketers in securing better job offers. The role of AI & ML in marketing is increasing due to the recent WFH (Work from Home) culture. Start learning AI and ML for productive marketing!

How Is a Machine Learning Course Helping Secure Bright Careers?

Posted on by Imarticus Learning

Machine Learning (ML) is an emerging technology that has taken businesses by storm. Currently, more than 30% of businesses in India have already adopted machine learning technology or are planning to adopt it. Besides being termed as the ‘hottest job of the century’, ML job roles also offer lucrative salaries.

ML along with AI (Artificial Intelligence), plays a crucial role in data science operations. Young enthusiasts are looking for ML/AI courses that offer them industry-oriented learning. Read on to know how an ML course can aid in building a successful career.

Reasons to learn ML & AI

 The reasons one should look for an industry-oriented ML course are as follows:

  • The compound annual growth rate of the global ML market is more than 40%. Businesses are adopting ML/AI technologies on a large scale. There will be no shortage of ML job roles in the industry for the coming years. Also, the salaries of ML job roles in the industry are expected to increase in the coming years.
  • ML and AI are versatile technologies that are used by different sectors of the industry. ML/AI algorithms are also used for day-to-day operations in many public sectors. Sectors like healthcare, logistics, e-commerce, education, and retail use ML for their day-to-day operations.
  • Machine learning helps in building smart data analysis algorithms. You can gain meaningful insights from data analysis and understand your customers/clients better. Data analysis skills will also come in handy for making several real-life decisions.

Why go for online ML training?

Colleges in India usually do not provide a certification course in AI or ML. AI/ML is usually included in the traditional degree programs as a subject. You will have to go through the entire degree program to learn machine learning at a college. It is where online training allows you to learn machine learning without enrolling in a degree program. Also, the recent COVID pandemic made it difficult for young enthusiasts to attend classroom lectures.

artificial intelligence and machine learning coursesWorking professionals can commit to an online machine learning course depending upon their free hours. However, you will have to choose an effective machine learning course that makes you job-ready. Imarticus Learning is a reliable EdTech firm that offers industry-oriented machine learning and artificial intelligence course.

Why choose the ML course offered by Imarticus?

Imarticus Learning is a reputed EdTech platform that offers a Certification in Artificial Intelligence and Machine Learning in partnership with IIT Guwahati. This 9-months long certification program can help in preparing for numerous jobs like ML/AI engineer, data analyst, and data scientist. The reasons one should choose the AI/ML certification course are as follows:

  • ai and ml courses
    At the end of the course, you will receive a certificate endorsed by ITT Guwahati, one of the top educational institutions in India. The AI/ML certificate endorsed by IIT Guwahati will be globally recognizable. Also, you will get a 3-day campus immersion program with this course that allows you to interact with faculty members and peers of IIT Guwahati.
  • You will work on more than 100 assignments and 25 projects during the course. Real-life projects will aid in learning the ML industry practices.
  • Numerous AI/ML topics will be covered in this certification course. Some popular topics covered in this course are dimensionality reduction, unsupervised learning, deep learning, NLP, etc.
  • Towards the end of the machine learning and artificial intelligence course, you will compete in a hackathon to judge your AI/ML skills. You will also receive career support towards the end of the course from Imarticus.

In a nutshell

Imarticus has already placed many data scientists in some of the top organizations of the world. With their industry-oriented course curriculum, they will make you job-ready. Start your ML certification course now!

What’s The Quickest Way To Learn Math For Machine Learning And Deep Learning?

Posted on by Imarticus Learning

In modern times we have everything from developments like smartphones, robots, driver-less cars, medical instruments like CAT scans and MRI machines, smart traffic lights, and a host of animated games. Even payments have gone digital and cashless! And all this has emerged over the last decade due to AI, ML, and data analytics.

The future holds great promise for development in these fields and to make a high-paid scope-filled career in any of these fields, mathematics is the key ingredient that you must learn if you want to learn machine learning. ML runs on algorithms and the algorithm is dependent on knowledge of mathematics and coding.

Why mathematics is so important in ML:

Some of the many reasons are :

  1. Selecting the apt algorithm with a mix of parameters including accuracy, model complexity, training time, number of features, number of parameters, and such.
  2. Selecting the validation of strategies and parameter-settings.
  3. Using the tradeoff of Bias-Variance in identifying under or overfitting.
  4. Estimating uncertainty and confidence intervals.

The math components required for ML:

ML algorithms require proficiency in the three topics of Linear Algebra, Probability Theory, and Multivariate Calculus.

Let us discuss the topics you need to learn machine learning under each of these heads.

A. Linear Algebra:

The use of Linear algebra notation in ML helps describe the structure of the ML algorithm and the parameters it depends on. Thus linear algebra is important in the interconnection of neural networks and their operations.

The topics that are important are : 

  • Vectors, Tensors, Scalars, Matrices,
  • Special Vectors and Matrices
  • Norms of Matrices
  • Eigenvalues and vectors

B. Multivariate Calculus:

ML learns from its experience with the data set and to supplement this we need calculus to power learning from examples, improving performance, and updating parameters of the different models.

The important topics here are : 

  • Integrals
  • Derivatives
  • Differential Operators
  • Gradients
  • Convex-Optimization

Probability Theory:

The assumptions about data use this theory to design the AI and its deep learning capabilities. The key probability distributions are crucial to algorithms.

Study these topics well.

  • Random Variables
  • Elements of Probability
  • Distributions
  • Special Random Variables
  • Variance and Expectation

Can you learn Math for ML quickly?

To learn machine learning it is not required to be an expert. Rather understand the concepts and applications of the math to ML. Doing things like math is time-consuming and laborious.

While there may be any number of resources online, Mathematics is best learned by solving problems and doing! You must undertake homework, assignments, and regular tests of your knowledge. One way of getting there quickly and easily is to do a learn machine learning course with a bootcamp for mathematics at Imarticus Learning

This will ensure the smooth transition of math and ML applications in a reputed institute for ML where they do conduct bootcamps. At the end of this course, you can build your algorithms and experiment with them in your projects. But, the main question that remains is why do a learn Machine Learning Course at Imarticus in the first place?

The Imarticus Learning course scores because: 

  • They have sufficient assignments, tests, hands-on practice, and bootcamps to help you revise and learn machine learning.
  • They use certified instructors and mentors drawn from the industry.
  • They integrate resume writing, personality development, mock interviews, and soft-skill development modules in the course.
  • They have convenient modes and timings to learn at your own pace for professionals and classroom mode for freshers and career aspirants.

Conclusion:

Mathematics is all about practice and more practice. However, it is crucial in today’s modern world where AI, ML, VR, AR, and CS rule. These sectors are where most career aspirants are seeking to make their careers, because of the ever-increasing demand for professionals and the fact that with an increase in data and the development of these core sectors, there are plentiful opportunities to land the well-paid jobs.

At the Imarticus, you can consider the Machine Learning course, you will find a variety of courses on offer for both the newbie and tech-geek wanting to go ahead in his/her career. Start today if you want to do a course in AI, ML, or Data Analytics. For more details in brief and further career counseling, you can also contact us through the Live Chat Support system or can even visit one of our training centers based in – Mumbai, Thane, Pune, Chennai, Hyderabad, Delhi, and Gurgaon.

TOP 10 APPLICATIONS OF DEEP LEARNING ARTIFICIAL INTELLIGENCE IN DIVERSE INDUSTRIES

Posted on by Imarticus Learning

Artificial Intelligence is the indispensable future. It is already in power and used by diverse industries like healthcare, education, and finance.

And now, deep learning has come as an addition to the next level of technological advancement. This blog post explores ten applications of artificial intelligence across different industries.

 TOP 10 BEST APPLICATIONS OF DEEP LEARNING

Virtual Assistants

AI Deep Learning has led to virtual assistants that understand natural languages; the best examples to quote being Siri, Alexa, and Google Assistant. The technology allows them to comprehend human speech more than before, turning everyday words into actionable data.

A virtual assistant is an application that handles day-to-day tasks and answers questions using artificial intelligence, natural language processing (NLP), and machine learning algorithms. Today, there are many popular virtual assistants: Amazon’s Alexa, Apple’s Siri; Microsoft Cortana; Google Now.

Chatbots

The chatbot has rules that use natural language processing to communicate with users. Chatbots can engage in one-on-one conversations and group chats on Facebook, Slack, or Telegram platforms.

Healthcare

Deep Learning & Artificial intelligence has found their application in diagnostics and healthcare. It combines the input of a large set of variables with historical patterns from similar cases to make accurate predictions on patient outcomes. It enables doctors to provide better diagnoses and personalized treatments.

Entertainment

Creators are using it to engage their audiences and create new experiences. For example, many music companies are using it for music composition. In contrast, other multimedia giants like Disney explore storytelling possibilities such as virtual reality movies or interactive games.

News Aggregation

A news aggregator is an application that collects articles, videos, and other content from different sources to organize it into categories.

Composing Music

Computer-generated music is possible because of AI methods. Such as generative adversarial networks (GAN). Computers can create new musical compositions inspired by those composed by humans.

Image Coloring

This technology is being used for image coloring as well. It is a visualization of an uncolored photo or artwork. It helps artists and designers understand how their work will look when it gets printed on paper.

Robotic

AI/ML and Deep Learning allow robots to learn from their own experiences by performing a task. For example, they can become more efficient at drilling holes in walls. Thus they perform the same action many times across different surfaces through deep reinforcement learning.

Automobiles

Automobile companies are also exploring the benefits of applying this technology to their cars. They have begun using computer vision and image processing techniques, which allow vehicles to learn how to drive over time by detecting any obstacles on the road. This technology helps prevent accidents as well as reduces traffic congestion through self-driving cars.

E-commerce

E-commerce uses it for product recommendations and helps consumers make better buying decisions. Thus providing them with a shopping experience based on their preferences and behavior patterns.

Why Enroll In AI Progam At Imarticus Learning

artificial intelligence courses in IndiaImarticus Learning offers Artificial Intelligence and machine learning courses that improve students’ foundational abilities.

Take advantage of the Expert Mentorship programs from Imarticus Learning to learn about Artificial Intelligence and Machine Learning in a real scenario.

This program enables you to gain access to attractive professional prospects in the disciplines of Artificial Intelligence and Machine Learning. This intensive 9-month curriculum prepares students for roles like data scientist, Data Analyst, Machine Learning Engineer, and AI Engineer.

Some course USPs:

  • The course lets the students learn job-relevant skills that prepare them for an exciting Data Science career.
  • Impress employers & showcase AI skills with a certification endorsed by the most prestigious academic collaborations of India – E&ICT Academy, IIT Guwahati, and Imarticus Learning.
  • World-Class Academic Professors to learn from through live online sessions and discussions. This will help students learn the practical implementation of AI/ML & Deep Learning techniques through real-world projects.
  • Flexible Learning Journey that gives you the flexibility to transfer program credits for a period of 1 year.

For further details, contact us through the Live chat support system or schedule a visit to training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Hyderabad, Delhi, and Gurgaon.

AI Deep Learning: What’s in it, and how is it an Asset for AI specialists!

Posted on by Imarticus Learning

Artificial Intelligence has seen exponential growth in recent years. AI is turning the way we live and work. But it cannot be easy to understand what exactly AI is. This blog post will tell you why to learn AI and why it matters for everyone!

What is AI deep learning?

Deep learning is a part of artificial intelligence and machine learning (ML) that imitates the way humans gain certain kinds of knowledge. This method has been around for several decades.

For AI, deep learning is a technique that allows artificial intelligence to learn and understand data. It works by showing an algorithm with lots of examples rather than programming it with inflexible rules, as many artificial intelligence programs have done in the past. Thus Artificial Intelligence and Machine Learning course helps to learn AI.

Why Is AI Deep Learning So Necessary?

While traditional artificial intelligence algorithms are linear, deep learning algorithms are stack in a hierarchy of increasing complexity and abstraction. Deep learning allows computers to connect concepts that they wouldn’t otherwise be able to do independently.

Artificial neural networks, algorithms get inspired by the human brain. They get trained from enormous volumes of data. The deep learning model would execute a task, modifying it each session to enhance the result, like how humans learn from experience. So, there is a need to understand AI.

How Is It Helpful For AI Specialists?

Deep learning allows artificial intelligence to identify patterns in data without human supervision. This artificial intelligence uses image recognition, which requires computers to understand concepts like color or objects and how they relate. Artificial Intelligence Course can be used to power self-driving cars and even recognize faces.

Artificial Intelligence (AI) is machine intelligence. Artificial Neural Network (ANN), Deep Learning, and Machine Learning are the most popular type of artificial intelligence at present. The ANNs algorithm creates a deep understanding of how to solve complex problems with computer data. Deep learning is a part of the artificial intelligence course. The IIT artificial intelligence Course helps to solve complex problems with data using neural networks.

Deep Learning is helpful for AI specialists working in different industries like Banking, finance, insurance, etc. It often gets used by all types of businesses and government sectors to solve problems.

Why Enroll In AI Progam At Imarticus Learning

artificial intelligence and machine learning courses in IndiaImarticus learning offers the best machine learning and AI course for your data science career. They provide certification in AI and Machine Learning. This 9-month Artificial Intelligence and Machine Learning program are in collaboration with AI/ML industry experts.

The program helps students to grasp precisely what Machine Learning and Artificial Intelligence market demands in professionals. Through 25 in-class real-world AI & ML projects, industry experts teach you crucial job-relevant skills.

Through several AI Deep Learning corporate strategies, students attain real-world Machine Learning and Deep Learning skills. The program is capable of converting a fresher into a highly prized New Age AI and ML Specialist. For further details on the course, contact us through the Live chat support system. You can visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Hyderabad, Delhi Gurgaon, and Ahmedabad.