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Category: Analytics

What Are The New Advancements In Data Analytics?

Posted on by Imarticus Learning

Data analytics is a field which witnesses a continuous revolution. Since data is becoming increasingly valuable with each passing time, it has been treated with great care and concern. New tools, techniques, theories, and trends are always introduced in the data analytics sector to cope with the constant changes in the industries and societies. You can opt for a sought-after data analytics course to get a deeper understanding.

In this article, we will go through some of the latest data analytics opportunities which have come up in the industry.

The Intelligent Data Mesh

The intelligent data mesh has been termed the next revolution in healthcare and medical diagnostics systems in the coming years by the Gartner Top 10 Strategic Technology Trends in 2018.

The “Intelligent Data Mesh” has been described by Gartner as a meeting point of the physical and digital worlds where humans, machines, data, and services have been entwined together into a mesh.

The purpose is to gather the benefits offered by all these individual entities into a single unit to find solutions to complex issues thought to be insolvable until now.

One major industry expected to benefit most from this system is the healthcare industry where Intelligent Data Mesh is being hailed as a game-changer in enhancing patient care.

Blockchain

Blockchain continues to be an exciting technology even in 2018 and is expected to remain so for at least another decade. New advancements are being made almost daily regarding this technology as blockchain finds wider uses in various industries with time.

It will not be wrong to describe blockchain as one of the greatest data analytics opportunities. The concept of blockchain started with the idea of a decentralized digital currency which came to be known as Bitcoin in the market.

However, even though the controversy regarding the currency rose the concept of a decentralized and open-source peer-to-peer modeled technology for storing and analysing data. The concept of blockchain is now applied in a wide range of industries with its use predicted to keep rising soon.

Artificial Intelligence

Artificial intelligence is one such data analytics opportunity which is finding widespread adoption in all businesses and decision-making applications. As per Gartner 2018, as much as 41 percent of organizations have already adopted AI into some aspect of their functioning while the remaining 59 percent are striving hard to do the same.

There is considerable research going on at present to incorporate artificial intelligence into the field of data science too. With data becoming larger and more complex with each passing minute, management of such data is getting out of manual capacities very soon. Scholars have now turned to AI for storing, handling, manipulating and managing larger chunks of data in a safe environment.

Augmented Reality

Augmented Reality is an interesting new technology coming up in recent years. As a source which facilitates the interaction between machine and humans in a unique manner, AR has the potential to be a game-changer in the field of data sciences making it another top data analytics opportunity in the future.
best big data analytics course

AR can provide for the development of simpler UIs for the man-machine interaction when merged with AI allowing the users to store and interact with data in a completely new manner.

Imagine going to an island where all your data is stored in different treasure chests and you are provided with customised keys to access the chests with your data in it. These things may be possible in the future because of the use of AR in data analytics. 

Imarticus Learning offers select best data analytics courses that not only boosts your skillset but also your career as a whole. 

Frequently Asked Questions

What is a data analytics course?

Data analytics involves examining raw data to extract valuable and actionable insights. These insights, once gleaned, serve as the basis for informed and strategic business decisions, contributing to the enhancement of overall business intelligence.

Do data analysts require coding?

Certainly, coding is a fundamental requirement when undertaking an online Data Analytics Degree. While highly advanced programming skills may be optional, mastering the basics of R and Python is crucial. Additionally, a solid command of querying languages such as SQL is indispensable for a comprehensive understanding of data analytics.

Is Python a mandate for data analysts?

Possessing a thorough grasp of Python programming proves highly advantageous for data analysts. Employers commonly anticipate proficiency in utilizing Python libraries to streamline various data-related tasks. Consequently, acquiring skills in Python emerges as a prudent and strategic career decision for aspiring data analysts.

Why is blockchain important in logistics management?

Posted on by Imarticus Learning

Blockchain is a new technology that will play an important role in logistics management. By utilizing Blockchain, we can streamline the process and reduce paperwork, time, and costs associated with international trade.

 Blockchain will also make it easier to track the status of shipments as they move from one country to another. This blog post will go through the overview of Blockchain and the benefits of using Blockchain in logistics management.

What is Blockchain?

Blockchain is an automated record-keeping system that makes it possible to improve supply chain efficiency, reduce costs and increase transparency. You can use Blockchain to track shipments across borders by recording the origin, destination, location, timestamps, and other essential data points. 

By utilizing distributed ledger technology (DLT), Blockchain creates an immutable and transparent record of all transactions. It allows for improved trust and collaboration among supply chain partners.

Blockchain is still a new technology, but several companies are already exploring its potential in logistics management. Blockchain has a lot of prospects to revolutionize the logistics industry, and we can see more companies adopting this technology in the coming years.

The benefits of using Blockchain in logistics management are:

  • Increased transparency and trust between supply chain partners
  • Faster, more accurate data sharing across the supply chain
  • Reduced costs and improved efficiency due to reduced paperwork and faster processing times
  • Greater visibility of the entire supply chain, from supplier to customer.
  • Improved security against cyber threats.

How to implement Blockchain in your business?

To implement Blockchain in your business, you need to understand how it works. First, a user or machine creates a block with a unique cryptographic hash. This block contains data and a reference to the previous block.

Blocks are chained together, forming a blockchain, which allows for secure and transparent recording of transactions. Every machine on the network has a full copy of the Blockchain to ensure all members agree and that no one can add or remove blocks without consensus from other network participants. 

This way, it’s impossible for someone to tamper with information recorded on the Blockchain because they would have to change every record across each block on the network.

The future of Blockchain in logistics management is bright. Blockchain technology may change a lot of supply chains across all industries in ways unimaginable today. Blockchain increases the transparency and trust among logistics managers, suppliers, and customers. 

Discover Supply chain Management course with Imarticus Learning.

The logistics and supply chain management course offers an experience beyond just classroom learning – our partnerships allow candidates interested in entering this hands-on field training from some of today’s top professionals!

Supply Chain Analytics is the key to making data-driven strategic, operational, and tactical decisions. 

Course Benefits For Learners:

  • We prepare students for a rewarding career in Supply Chain Management and Analytics by immersing themselves in in-demand tools and projects, including six real-world projects that will provide them with a thorough understanding of the sector. 

     

  • Supply chain management online course prepares students for competitive jobs such as Demand Planner or Data Scientist, which employers today have in high demand! 
  • By utilizing the power of Python, this course will help students become more data-centric and enhance Supply Chain decision-making.

Understanding regularization in machine learning

Posted on by Imarticus Learning

A machine learning model is a set of algorithm expressions that understands and analyses mounds of data to make predictions. Why is it that sometimes a machine learning model does great on training data but not so well on unseen data? It happens because, at times, this model becomes an overfitted model or even an under-fitted one.

Data fitting is very crucial for the success of this model. In this model, we plot a series of data points and draw the best line towards the relationship between the variables. 

This model becomes an overfitting one when it gathers the details with the noise present in the data and tries to fit them on the curve. 

The underfitting model neither learns the relationship between variables nor classifies a new data point. At Imarticus, we help you learn machine learning with python so that you can avoid unnecessary noise patterns and random data points. This program makes you an Analytics so you can prepare an optimal model. 

Meaning and Function of Regularization in Machine Learning

When a model becomes overfitted or under fitted, it fails to solve its purpose. Therefore, at Imarticus, we teach you the most crucial technique of optimal machine learning. In this program, we coach you to become an Analytics by learning the procedures to add additional information to the existing model. 

In the regularisation technique, you increase the model’s flexibility by keeping the same number of variables but at the same time reducing the magnitude of independent variables. This technique gives flexibility to the model and also maintains its generalization.

Regularization Techniques

The regularization techniques prevent machine learning algorithms from overfitting. It is possible to avoid overfitting in the existing model by adding a penalizing term in the cost function that gives a higher penalty to the complex curves. Regularization reduces the model variance without any substantial increase in bias. Python classes also help in this technique.

To become an Analytics, you have to understand these two main types of regularizations:

  • Ridge Regression
  • Lasso Regression

Ridge Regression:

In this type of regularization, we introduce a small amount of Ridge regression penalty bias for a better long-term prediction. It solves the problems when the parameters are more than the samples. It decreases the complexity of the model without reducing the number of variables. Though this regression will shrink the coefficients to the least dominant predictors, it will never make them zero.

Lasso Regression:

In this regularization technique, we reduce the complexity of the model. The penalty weight includes the absolute weight in the Least Absolute and Selection Operator. The coefficient estimate equals zero, and it provides the feature selection. 

But, if predictors are more than the data points, this model will pick non-zero predictors. This model also selects the highly collinear variables randomly. 

Data Analytics Certification 

The certification in AIML will train you as an Analytics. It will help you understand how regularization works. After completing the certification program at Imarticus, you will know to shrink or regularise the estimates to zero. You can also enhance the model that can accurately calculate the data.

Why Senior Leaders Must Take Lead For Cybersecurity Across Businesses?

Posted on by Imarticus Learning

With the increase in technological advancement, being up to date with all the trends in technology is important for businesses to stay in the fast-paced race of today’s market. Along with upgrading systems, businesses need to pay very careful attention to their cyberspace which means enhancing cybersecurity.

Cybersecurity is extremely important to protect vital information and assets belonging to a particular business. This would require company leaders and senior executives to strategize and protect the company from the now frequently happening data breaches as well as cyber-attacks.

Cybersecurity Training CourseIn order to drive more informed investing procedures and resourcing methods along with increased efficiency and resilience, it is looked on to senior company officials to make good strategic decisions and protect the company from any threats. When we say senior executives it includes C-suite officials as well as policy-makers.

It is not a secret anymore but a well-known fact that in the digital frame that the world is functioning in today, cybersecurity should be among the top priorities for any and all businesses. However, a number of issues of both organizational as well as structural nature pose as obstacles for the establishment of cybersecurity models that are driven by business and that focus on risk management.

Hence, only a continued support shown by officials in the upper and top management positions of any organization would allow the decrease in cyber risks and increase in progress and growth.

What Would Incorporating Cybersecurity Mean for Senior Leaders?

In every organization or company, there are people at the top that are held accountable for making important decisions which would set the course and direction for the company to follow in. Their duties also involve holding ground on priorities, maintaining and influencing the company as well as preventing risks. They are thus basically responsible for the healthy functioning of the organization, company, business or establishment.

As mentioned above cybersecurity, in this fast-changing and fast-moving business environment, is the main concern for all organizations. Thus decisions taken regarding cybersecurity are left to the decision-makers of the company. Their duties now would include:

● Managing and decreasing cyber-related risks to the business while setting up effective methods of governance
● Making cybersecurity programs a priority and focusing on resourcing
● Managing and protecting vital information that holds the business together when it comes to planning
● Encouraging cybersecurity from within

This is all very important in order to promote organizational growth through the protection of digital assets and delicate data information. Executives at the top thus need to gain a better understanding of cybersecurity and this can be easily done through cybersecurity training which would help them understand what exactly can be a risk to their organization.

This understanding would in turn help in making rational decisions in a timely manner. It would also promote resourcefulness and strategic thinking.

A cybersecurity training course would thus also help further the artificial intelligence and machine learning career of aspirants by equipping them with all the necessary skills and information that they would need.

Supply chain management courses on the rise catalyzing blockchain to leverage potential

Posted on by Imarticus Learning

Implementing blockchain technology is a new and promising way to present opportunities to improve the supply chain and related management process of any company. Notably, blockchain is a distributed database that is specifically used for the electronic storage of information that cannot be changed or deleted.

In the supply chain, the implementation of blockchain technology indeed gives it an added boost in order to improve the traceability and transparency in the supply chain as well as to reduce unnecessary administrative costs. 

Blockchain has gained global popularity. Many startups and corporations are also considering venturing into the use of this technology outside the industry of financial services. An example is Provenance, which is a startup specializing in supply chain transparency and finished a 6-month pilot project for keeping a track of the reliable tuna sourcing in Indonesia through blockchain. 

How has blockchain been integrated into the supply chain management system?

Blockchain in the supply chain is still under the experimental stage. And so far, it has helped participants record important relevant information like price, location, certification, date, and quality to efficiently run the supply chain management system. The availability of such information within the blockchain system increases the traceability of the material in the supply chain and reduces the chance of losses. It further enhances the organization’s position as a leader in reliable manufacturing. 

Top blockchain in supply chain management courses online

Blockchain will most likely dominate the supply chain industry due to it streamlining the processes involved. This will create a demand for more blockchain developers in the supply management industry. If you are looking for some reliable courses, then here are a few:

Blockchain in supply chain management: In this course, you will learn the ways in which blockchain technology is being implemented in supply chain management to efficiently deliver secure and transparent supply chains. You will be given in-depth knowledge of what blockchain is and how it has been implemented in supply chain management (SCM). You will additionally get to explore actual business use cases where blockchain is applied in SCM. You will be taught the necessary steps for implementing blockchain in your supply chain. 

 

Certified supply chain professional and blockchain training: Blockchain is a disruptive technology that has been deployed in a multitude of domains to optimize countless processes. Since there is a rising demand for blockchain professionals in the supply chain industry, a special certification is a proof that you are more competent and are sure to have an advantage over others.

This course is designed to guide anyone in creating solutions that can have an impact in every possible facet of the supply chain. It is professional training that deals with providing you with the necessary knowledge of how blockchain can be utilized for increasing revenue, decreasing costs, and improving other factors like quality and production.

 

Needless to say, there is a rising demand for blockchain developers and experts. And in the coming years, it has the potential to provide prospects to individuals just starting off. A supply chain management career is one of the best fields to venture into and is highly promising with a good amount of job satisfaction. Therefore, if you want a supply chain certification to kickstart your career in the domain, then you can opt for a good supply chain analytics course.

Adopting a data-driven approach to supply chain certification courses

Posted on by Imarticus Learning

Supply chain analytics is an integral part of SCM (supply chain management) which is entirely data-driven. It primarily depends on gaining insights and values from the huge amounts of data related to various supply chains management elements like procurement, processing, and distribution of commodities. 

Further, supply chain analytics is involved in the collection and compilation of relevant data from across various applications, third-party sources, infrastructure, and upcoming technologies. This improves the quality of tactical and strategic decision-making in supply chain management. You can get better at it by enrolling in a comprehensive supply chain certification course. 

Besides, supply chain analytics also aids in the synchronization of planning and execution by enhancing real-time visibility into these methods and the impact they have on customers. Increased visibility leads to the increase in flexibility in a supply chain network that eventually helps decision-makers to efficiently evaluate tradeoffs amongst customer service and the cost.

How is supply chain analytics related to supply chain management?

Supply chain analytics plays an integral part in supply chain management because it has the ability to think about and make data-driven decisions on the basis of the summary of trusted and relevant data. Since supply chains generate huge amounts of data, supply chain analytics decipher the data to make sense of it and uncover insights and patterns. This is how supply chain management is dependent on supply chain analysis. 

Courses related to supply chain analytics

We can already conclude that a supply chain cannot exist without supply chain analysis. If you are enthusiastic about supply chain management as well as data analysis, then here are some courses that will give you a better insight into the data-driven approach to supply chain management. 

Supply chain analytics certification: This course is meant for individuals who want to learn about how to integrate supply chain management with data analytics. It will help you discover, determine and solve problems in various sectors of a supply chain. Additionally, you will develop data analytics skills and learn how to use tools for improving supply chain performance.

 

Big data analysis and machine learning: This certification will give you added leverage as you will be taught how to use most of the data science tools and techniques that are in demand to make yourself ready for the job market. You will develop important and valuable skills in Python, data analytics, SQL, data visualization with Tableau, and machine learning.

Real industry problems with real industry projects: A business analyst’s role is to prescribe the ultimate solution to any problem and this analytics course emphasises teaching and building up this quality. This course will teach you how to take data and models and connect them to real-world scenarios requiring decision-making in the supply chain and other areas like finance, manufacturing, and human resource management.

Predictive analytics for demand forecasting: Data is the basic raw material that is highly dependent on predictive analysis for understanding it and effectively utilizing it. This specialization helps learners recognize the primary components of predictive analysis which include monitoring big data at any given moment.

It also teaches the importance of Tableau that provides particular views of minuscule events or connects information to the recent forecasts and trends in order to ensure efficient allocation of resources and improve effectiveness.

Supply chain management is a job role that also requires the efficient handling of large amounts of data sometimes. Professional certification in supply chain management or any top-tier supply chain certification will help in acquiring the necessary skills to fit the bill.

It ought to equip you with the knowledge and skillsets that you will require in your journey into supply chain management. You can opt for good courses offering certification in supply chain management online with Imarticus Learning.

How to get started in Python: An overview of recent trends

Posted on by Imarticus Learning

Are you very interested in programming? Then you need to know the programming language Python. No, it’s not exactly about pythons and snakes, so you can let your puppy loose.

Why Python, specifically? It’s approachable, simple, and adaptable to a range of situations. And because a growing number of programmers all around the world are using and appreciating it.

In fact, according to a recent rating published by IEEE Spectrum (a prestigious engineering and applied science newspaper), Python will be the most used programming language in 2020, followed by JavaScript, C++, C, and Java.

Python’s popularity has been stable in recent years, and this trend is unlikely to reverse. Python tutorials are the most popular on Google, according to the PYPL portal, and everyone wants to learn Python nowadays.  

This explains why Dropbox, Netflix, Facebook, Pinterest, Instagram, and Google all employ Python in their technical growth. Additionally, NASA is included in this list of “tech celebrities” that use Python. Do you see why it’s important for you to be aware of it?

Python is quite popular, and everyone wants to learn more about it. You, too, would not be reading this article if you weren’t.

Projects and programs made in Python

  • Netflix

Netflix, the platform that had a growth of 16 million subscribers during the first quarter of 2020, also uses Python. Its engineers prefer this programming language mainly because of its available libraries.

  • Instagram

Yes, the app you use to share images frequently uses the Python programming language on its backend (what runs on a server). In other words, Instagram is implemented on the open-source web development framework Django which is written entirely in Python.

  • Google

This is one of the big projects that also use the Python programming language, in addition to C++ and Java.

What are the characteristics of Python?

The Python programming language is known for being simple, quick, and having a short and easy learning curve. It is free to use and share because it was created under an open-source license.

But what does “multi-platform”, “multi-paradigm” and “interpreted” mean, here is the explanation:

– Multi-platform: Python can operate on a variety of platforms, including Windows, Mac OS X, Linux, and Unix.

– Multiparadigm: Because it is a programming language that allows a variety of programming paradigms (development models), programmers are not forced to utilize a particular style. Python supports which programming paradigms? Programming styles include object-oriented, imperative, and functional programming.

– Interpreted: Python “interprets” the programmer’s code, which implies it both interprets and executes it.

Python may also be used as an extension language for applications that require a programmable interface since it is dynamically typed (when a variable can take values of multiple kinds or adapts to what we write).

What is Python and what is it for?

Python is a multi-paradigm, multi-platform interpreted programming language used mostly in Big Data, Artificial Intelligence (AI), Data Science, testing frameworks, and web development. Due to its vast library, which has a wide range of features, it qualifies as a high-level general-purpose language.

In 1989, Guido van Rossum, a Dutch programmer, decided to construct an interpreter for a new scripting language he was developing.

His significant expertise in creating the ABC system – an interactive, structured, high-level programming language – aided his efforts to develop a language that was more intuitive, simpler, more powerful. Python, the successor of the ABC language, was born in 1991 (yep, he is a millennial at 29 years old).

Conclusion

At Imarticus we offer a Data Analytics course where you will learn more about how to get started in Python and you will receive more than an overview of recent trends. Visit our website today and enroll in one of our analytics programs. 

Vectors are over, hashes are the future of artificial intelligence

Posted on by Imarticus Learning

AI (artificial intelligence) aims to have computers capable of thinking independently. We are getting closer to achieving that goal, but there are some obstacles in the way. One problem is how computers understand language and communicate with humans. This blog post will discuss how hashes are the future of Artificial Intelligence.

What are vectors and hashes, and how do they differ?

Vectors are a mathematical structure that represents multiple values as a single entity. You can use Vectors in artificial intelligence for matrix multiplication and deep learning tasks. On the other hand, Hashes are a data structure that can store an object’s key-value pairs. You can use hashes in computer science for caching and data mining tasks.

Vectors are better for tasks that require large amounts of data, while hashes are better for jobs that require a small amount of data. For example, vectors are used in deep learning because they can handle a lot of data. Hashes are used in data mining because they can take a small amount of data.

Why are hashes becoming more popular in the world of AI development?

You can use them to teach computers about the environment around them. It’s easy for machines to see what something looks like, but it is much more difficult for them to understand how that object will act in specific scenarios without prior experience. It means hashes can provide a foundation of knowledge that AI systems can understand.

Most importantly, hashes offer a way to understand how the world works without requiring large amounts of data. It is essential because it takes multiple datasets to train neural networks for AI development, and those can be difficult to obtain in some cases.

How can hashes be used to improve the accuracy and efficiency of AI systems?

One way hashes can improve the accuracy and efficiency of AI systems is by reducing the number of dimensions in a vector space. In other words, hashes can help reduce the complexity of data while still preserving its information content. Additionally, you can use hashes as a form of error detection and correction. Incorporating checksums into hash algorithms makes it possible to detect and correct data errors without recomputing the hash.

It can be beneficial for large datasets that are difficult to process in their entirety. Finally, you can use hashes as a form of compression. By representing data as a series of hashes, it is possible to reduce the size of the data while still retaining its information content.

Explore and Learn AI with Imarticus Learning

The Artificial Intelligence certification program collaborates with the E&ICT Academy, IIT Guwahati, and industry professionals to deliver the most satisfactory learning experience for aspiring Artificial Intelligence and Machine Learning students. This curriculum will prepare students for a data scientist, Data Analyst, Machine Learning Engineer, and AI Engineer.

Course Benefits For Learners:

  • This Artificial Intelligence course will help students improve their Artificial Intelligence basic abilities.
  • Students can now take advantage of an Expert Mentorship program to learn about Artificial Intelligence and Machine Learning in a practical setting.
  • This course will assist students in gaining access to attractive professional prospects in the disciplines of Artificial Intelligence and Machine Learning.

Changing career paths: A developer’s journey towards supply chain management courses

Posted on by Imarticus Learning

To meet the demand of a customer for a product or service, there is a chain of procedures involved such as Sourcing, Warehouse, Distribution, and the like. Effective management of these processes is called Supply Chain Management. Supply Chain Management is crucial in most businesses where professionals are required to manage and handle not only the flow of information but most importantly the flow of their products, as per the behavioural changes in consumers.

Just like changing industrial trends and customer behaviour, career paths are subject to change as well. You may find interest in a supply chain as a career even without any qualification or formal training and even if you are from a different industry and a different sphere. As impossible and risky as it may seem, all it takes is having faith in yourself. Here are some skills you will require to excel in Supply Chain Management.

Mandatory Supply Chain Management Skills:

  1. Creative Mindset: You need to come up with unique ways to improve your current role and also help reduce waste. 
  2. Have Computer Skills And Knowledge of Data Management:  You will need good computer skills to handle, understand, analyze, utilize, and manage data. 
  3. High Learning Aptitude: You will need to learn new concepts on the daily basis and use them to improve the process. 
  4. Working in a Team and Leadership Skills:  Supply Chain Management requires good leadership and management skills to not only manage tasks but also improve the efficiency of the team as well. 
  5. Customer Service Skills: Supply chain managers are required to make client rosters. To build such relationships with the suppliers, excellent customer service skills are a must-have. 
  6. Enterprise resource planning (ERP) mastery: Supply Chain Managers use ERP software to execute their job and you can attain these high-level skills through training on the job and tutorials or a certificate course in supply chain management.

Why Take-up SCM Courses?

For a detailed introduction to the world of Supply Chain Management, it is highly recommended that you take up a Supply chain Management course especially if you are planning to change your career field. It will give you a better understanding of how it works and the various complexities related to it in today’s global networked economy. 

A specialization in Supply Chain Management is made up of four courses. They are in operations, logistics, sourcing, planning, and strategy. A Supply Chain Management course will not only help you develop the aforementioned points, but also will cover the technical aspects required to optimize flow, and also the Lean practices and Six Sigma quality. You will gain vast knowledge on various forecasting techniques, and also how to create reliable and productive relationships with suppliers. 

Great Career Opportunities Supply Chain Management (SCM) Courses Provide

A Qualification in Supply Chain Management (SCM) provides a plethora of opportunities and the job roles are as follows. 

  1. Purchase Manager: A Purchase Manager is required to procure goods and services. 
  2. Strategic Planner: The job role of a Strategic Planner involves planning and coming up with a business strategy. 
  3. Materials Analyst: A Material analyst is required to make sure that the flow of goods and services amongst a company’s distribution chains go seamlessly. 
  4. Supply Chain Manager: Supply chain management is the main man in the manufacturing process. 
  5. Warehousing Manager: Warehouse managers are required to manage things like storage, receipt, and dispatch of the goods. 

Conclusion:

A career in Supply Chain Management ought to take you places. A reliable supply chain management training course is what you will need to kick-start your SCM journey to success. Keeping in mind the points mentioned above. 

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.