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Tag: best artificial intelligence and machine learning courses by E&ICT Academy

Developing digital health care solutions with an artificial intelligence and machine learning course

Posted on by Imarticus Learning

In the current times, digitization is seen in every sector, and healthcare organizations are not far behind. Artificial intelligence with machine learning and algorithms is the newest aspect of the technological developments that can help to automate various processes.

If you are interested in implementing AI in healthcare, you can opt for Imarticus Learning’s artificial intelligence and machine learning course. The course includes relevant use of technology across industries, including healthcare. 

How to Implement Artificial Intelligence and Machine Learning in Healthcare? 

Artificial intelligence has various roles in the healthcare industry. If you choose to get an artificial intelligence certification, you will learn more about the following aspects. 

 

  • Prediction of Treatments

 

Artificial intelligence and machine learning can be implemented for the accurate analysis of patient information. AI solutions can analyse medical conditions and help doctors arrive at accurate treatment plans that will be beneficial to the patients. While reviewing all medical information is necessary for correct diagnosis, doing so manually increases workload and may even lead to errors. Artificial intelligence and machine learning can automate specific processes and ensure error-free treatment plans. 

 

  • Improvement of Workflow

 

From the IT infrastructure in healthcare organizations to diagnostic tasks, workflows can be automated and optimized. This will improve business processes and ensure better outcomes. All organizational tasks will be seamless and less time-consuming. 

 

  • Detection of Anomalies

 

Most healthcare organizations include digital databases and rely on workflow automation. While AI can assist in automation, it can also monitor the entire system. Failure of systems in any industry leads to loss, however, in the healthcare industry, anomalies can lead to loss of lives and not just revenue. Therefore, it is important to use artificial intelligence and machine learning tools to detect gaps within the system so that professionals can take better precautions. 

 

  • Introduction of Opportunities for Clinical Trials

 

While artificial intelligence solutions are capable of predicting treatment plans through a thorough analysis of symptoms, they can also assist in clinical trials. Artificial intelligence can be used to determine if certain patients are suitable candidates for trials. Such solutions can also help doctors predict patient responses to trials. AI and machine learning create space for safer clinical trials by ensuring that patients can withstand treatments. 

How Can Imarticus Learning’s Al ML Course Prepare You for a Career in Healthcare? 

If you wish to enter the healthcare sector and work in the digitization of healthcare solutions, then Imarticus Learning’s Certification in Artificial Intelligence & Machine Learning is a great option. Our course is in collaboration with E&ICT Academy and IIT Guwahati. So, you will have access to lectures and curricula designed by renowned academicians and industry professionals.

At Imarticus Learning, we ensure that the IIT AI ML course prepares students for a long and rewarding career in data science and machine learning engineering. You will be attending live sessions for eight hours every week and we encourage you to interact with all teachers and peers. Imarticus Learning creates opportunities for students to network and hones their soft skills while preparing for work in the industry.

To ensure hands-on experience, we offer twenty-five projects that are based on real business issues and more than one hundred assignments. 

The certificate course in artificial intelligence and machine learning at Imarticus Learning is ideal for students who have completed graduation in computer science, engineering, statistics, mathematics, science, or economics. If you have a minimum of 50%, you can enroll in our program and receive education and industry training from experts.

The fourth Industrial Revolution: a primer on computer vision tutorial

Posted on by Imarticus Learning

The fourth Industrial Revolution is upon us, and it’s bringing a new wave of technological innovations. This post will explore the basics of computer vision, one of the most exciting technologies to come out in recent years.

It’s a branch of artificial intelligence that understands scenes from images or videos. With computer vision, you can quickly identify objects in pictures and recognize what is happening at different locations by looking at them! You can use it for applications such as face recognition, navigation assistance, and many more!

What is computer vision, and what are its applications?

Computer Vision = Artificial Intelligence + Machine Learning

AI is particularly interested in solving problems by building machines capable of intelligent behavior, learning from data, and taking action based on what they’ve learned. And machine learning is a subset of artificial intelligence concerned with the design and development of algorithms that can access data.

Computer vision tutorial is a field in which computer scientists apply their knowledge of imaging, mathematics, physics, engineering, visual perception, and computing to develop methods and algorithms so computers can visually understand scenes. It involves extracting information from a single image or a sequence of images.

From an engineering perspective, you can apply computer vision tutorials to understand and analyze areas such as video surveillance, medical imaging, document management/image retrieval, automatic facial recognition systems for security, etc. You can use it in autonomous vehicles. A fundamental component enables a car to understand its surroundings and make intelligent navigation decisions.

Applications of computer vision:

Automatic Facial Recognition

One of the most common computer vision applications is automatic facial recognition. An image of a person’s face is captured and then used to identify that person from a database of images. You can use this application for security purposes.

Video Surveillance

You can use computer vision to monitor and capture events occurring in video surveillance automatically. You can find this application at airports, casinos/gambling venues, shopping centers, and other places of interest where security and safety are concerned (e.g., amusement parks).

Automotive

Computer vision is used in automotive applications to help the car avoid obstacles and driver assistance systems. Driving a vehicle without using computer vision would be virtually impossible, given that there are just too many visual variables for a person to take into account at any one time. 

Medical Imaging

Computer vision is used in medical imaging to help doctors diagnose and treat patients. You can use computer vision to automatically identify lesions on the skin or tumors inside the body.

Explore and Learn AI Deep Learning with Imarticus Learning

This intensive course will prepare students for a data scientist, Data Analyst, Machine Learning Engineer, and AI Engineer. Students can now utilize our real-world projects from a variety of sectors. This course will assist students in gaining access to attractive professional prospects in the disciplines of Artificial Intelligence and Machine Learning.

Course Benefit For Learner: 

  • Learn machine learning skills by participating in 25 in-class real-world projects and case studies from business partners. 
  • This AIML course will provide students with a strong understanding of data analytics and machine learning fundamentals and introduce some popular tools used by professionals today. 
  • Students can now take advantage of our Expert Mentorship program to learn about Artificial Intelligence and Machine Learning in a practical setting. 

What is Supervised learning?

Posted on by Imarticus Learning

Supervised Learning is a machine learning method that makes predictions based on input data. It’s one of the most popular methods for predictive analytics because you can use it to make accurate predictions and analyze trends in the data. This blog post will discuss supervised Learning and how it can help you improve your business!

What do you mean by supervised Learning?

In simple terms, it is a standard machine learning algorithm that uses labeled training data to predict the output. Supervised Learning applies predictive modeling techniques on large datasets/data streams to find patterns and relationships between features, which you can use for building accurate models.

Supervised learning algorithms are a common way to make predictions when there is data on both the input and output sides. The algorithm will learn to map the input variables to the desired output variable by using a training set of example data. You can use supervised learning algorithms in various industries and applications. 

How does it work?

Supervised Learning is an algorithm that can learn from data with answers labeled correctly. The algorithm consists of training data with several input values (x) and the corresponding desired output value (y). It then predicts the output for new inputs.

You can use supervised learning algorithms for a wide range of tasks, such as:

  • Classification: Determining the type of object an image contains, such as a cat or a dog.
  • Regression: Predicting a value, such as the price of a house or the number of calories in food.
  • Clustering: Grouping data into clusters based on similarities.

There are many different supervised learning algorithms, each with strengths and weaknesses. Popular ones include linear regression, logistic regression, support vector machines, and neural networks. Choosing the correct algorithm for your task is essential for achieving good results.

Why should you use supervised Learning to train your models?

Supervised Learning is a machine-learning method that enables us to obtain the parameters of an algorithm from labeled training data. We have a set of input and output pairs with known labels. The goal is to learn from these examples to correctly map new inputs onto their correct outputs when given previously unseen instances.

The most common example of a supervised learning problem is the classification task that labels our data with more classes. In this case, samples typically get drawn from labeled training sets, and each label corresponds to a class (or multiple disjoint classes). The critical point is that tags associated with different inputs must be read-only (immutable).

Discover AIML certification with Imarticus Learning

This Machine learning course will give students a solid grounding in the practical applications of data science by teaching them how to use these skills to solve real-world problems. This program is for graduates and early-career professionals who want to further their careers in Data Science and Analytics, the most in-demand job skill.

Course Benefit For Learner: 

  • Learn machine learning skills by participating in 25 in-class real-world projects and case studies from business partners. 
  • This machine learning course will provide students with a strong understanding of data analytics and machine learning fundamentals and introduce some popular tools used by professionals today. 
  • Impress employers & showcase skills with AIML course recognized by India’s prestigious academic collaborations.

Here’s why music created by AI is better than you think

Posted on by Imarticus Learning

Artificial Intelligence or AI is capable of carrying out tasks that are much more advanced than just arranging words to generate lyrics. AI already has the ability to offer an immersive listening experience by adapting to a user’s preference. As seen in Spotify and Apple Music for a long time, AI systems understand the user’s preference and recommend songs that the user will enjoy.

AI has gone a step further and now is also able to compose completely personalized music for users. AI can understand certain benchmarks such as harmony, structure, and balance, using which, AI models can generate songs or background music based on the input provided by the user.

Is AI Capable of Creating Better Music Than Humans?

If AI is able to compose music without human supervision, people who need background tracks or copyright-free songs might not need music producers or artists as much as they currently do. Purchasing AI-created music also is easier as there are no royalties while the music generation process would be faster and available on demand.

Yes, with vast amounts of data and training, AI can help in creating a very capable autonomous music generation system, however, it will still be relying on historic data and other pieces of music in order to generate future songs. But, due to the vast amount of data available, the probabilities are limitless and if taught to truly identify good music, AI can become capable of generating hit songs one after another using the very same data.

Even coming up with new songs are just mathematical likelihoods for AI and by analyzing enough combinations, AI is bound to come up with good music. Similarly, meaningful lyrics can also be generated with Natural Language Processing or NLP. However, it will take a while till AI systems become as sensitive to the context of lyrics and innovative in using musical notes.

How AI is Helping in Creating Music?

Even though completely AI-generated music has not reached the Billboards Top 10 yet, services such as AIVA uses AI and Deep Learning models for composing soundtracks and music for users. This helps both small content creators and mainstream celebrities generate music for YouTube, Tik Tok, Twitch or Instagram. This is a cheaper alternative as well. Amper is another great online tool for content creators and non-musicians to make royalty-free music based on their own preferences and parameters. Amper has been created by the music composers who are behind creating the soundtrack for movies such as ‘The Dark Knight’. 

Alex the Kid is a UK-based Grammy-nominated music producer who has used ‘heartbreak’ as a theme and with the help of Machine Learning (ML) and Analytics, has created the hit song ‘Not Easy’. The song even features celebrity music artists such as Wiz Khalifa, Sam Harris, and Elle King.

The hit song had reached the 4th rank in iTunes’ ‘Hot Tracks’ chart within 2 days of its release. Alex used IBM Watson for analyzing billboard songs of the last 5 years as well as cultural and socially relevant content, scripts, or artifacts in order for including references to these elements within the song. Then, the producer used Watson BEAT, the ML-driven music generation algorithm powering the cognitive system for coming up with various musical backgrounds till he found the most suitable combination. 

Conclusion

Artificial intelligence and Machine learning courses can definitely help one learn AI topics for getting involved in interesting projects such as those mentioned above. A Machine Learning and Artificial Intelligence course, such as one offered by Imarticus, are essential for building AI systems such as soundtrack generators or lyrics generators.