What is the Scope of Scrum master?

Posted on September 13, 2021September 13, 2021 by Imarticus Learning

Scrum
Scrum is a framework that helps different teams to work in a cohesive manner. Scrum helps teams to remain self-organized while dealing with a problem. Using the Scrum framework, teams learn from their experiences. Scrum enables effective use of all the available resources and makes the deliverables available with high efficiency.

Scrum helps in dividing the overall projects into various sub-projects referred to as sprints. The use of scrum empowers all the team members to have visibility of everything happening in the project. The use of scrum makes it possible to have a 3600 feedback system regularly. Along with the performance and efficiency of the entire team, Scrum also focuses on the individual performers in the team.

Scrum Master
The scrum team leader, also referred to as the scrum master is a person who takes care of to and for communication between the product owner and the entire team members, communication within the team, without actually being included in the strategy flow of the product. Along with smooth communication, scrum master also ensure that all the team members follow astute values.

Scrum Master Course

Who should attend the Scrum Master Course?
The Scrum Master course is meant for the professionals who use the Scrum framework to develop software and the professionals whose ultimate commitment at the workplace to maximize the Scrum

Scrum master Course-Competencies

Competency 1 – Scrum values

Clear focus, Respect, commitment, and courage are the key values possessed by a Scrum master. The ability to apply the stated values in the organizations with the different sets of values altogether defines the role of the Scrum master. Practitioners living with the scrum values help create an environment where continual improvement with self-organization continuously flourishes.

Competency 2 – Empiricist Philosophy

Practicing Empiricist Philosophy to solve problems is the essential quality of the scrum master. The entire philosophy talks about breaking the complex problems into various incremental problems for empirical execution. The use of scientific methods to solve complex problems is the key attribute of empirical philosophy.

Competency 3- Scaling

The design of the Scrum framework helps to achieve the individual targets at the team, product, and organizational levels. The practitioner has a complete understanding of all the scales and the levels of the scrum. Different levels of scaling can be used in complex frameworks, keeping the essential qualities of scrum such as empiricism and continuous improvement intact.

Competency 4 – Events

The entire Scrum framework is defined in 5 stages. Sprint is the first stage, followed by sprint planning. The entire sprint planning defines the third, fourth, and fifth stage which is daily scrum, sprint review, and sprint retrospective respectively. These time-bounded stages facilitate the progress and achievement of goals through transparency. The three pillars of Scrum i.e. transparency, inspection, and adaptation uphold the entire system.

Competency 5 – Sprint-Product Backlog and Increment

Product and sprint provide the team with materials to plan, execute and review the sprint deliverables. Professionals in the same field will understand the application of these facts in real and complex situations, hence integrating the facts with the organization’s own objectives.

Competency 6 – ‘Done’
‘Done’ (DoD) is defined by the practitioner as the focus area to be applied to the particular context. The same needs to be communicated and visualized internally in the organization. The practitioner will be able to describe the trade-offs and compromises to be considered to deliver ‘done’.

Scrum master Salary in India
Average salary of Scrum Master in India is Rs.1,412,000 per annum which range between Rs.2,268,000 and Rs.7,02,000. Factors that determine the salary range for a candidate are experience in the field, region, and the company’s profile. Favorable factors decide the inclination towards the higher spectrum of the salary.

How Edge IoT Solutions Can Improve Business Performance?

Posted on September 10, 2021March 22, 2024 by Imarticus Learning

Artificial Intelligence (AI) and Internet of Things (IoT) technologies are transforming the ways of business entirely. The power of these technologies is revolutionizing the business sphere by evolving its chief resources such as software, products, applications, and overall systems.

AI and IoT are becoming widespread as businesses are looking for ways to hyper-optimize their performance by propelling the value-addition processes and generating better results from data through connected devices.

AI and IoT help companies to find patterns not easily identified by humans. It enhances operational capacity and boosts the production of products and services. By implementing AI and IoT businesses mitigate their risks and improve their efficiency.

That is why companies today are investing heavily in the digitalization of their businesses.

They are employing new technologies and experts with an artificial intelligence and machine learning career to help them achieve optimal performance levels.

AI at the Edge

Artificial Intelligence at the edge is the intelligence that is influencing the retail and semi-autonomous car businesses at large. These technologies are diminishing the data communication costs and allowing instantaneous business operations which comprise decision-making, information creation, and action-taking. The real-time processing in AI at the Edge is vital for many operations in robots and semi-autonomous vehicles, etc.

A high amount of computational power is required by many Edge AI technologies. When the latency and instantaneous response process is low Edge AI becomes crucial for businesses. Through these Edge AI technologies, businesses get to mitigate their risks, detect problems, and find solutions to resolve issues.

Attaining Business Values

The AI at the Edge solutions helps businesses improve their functional capability and, hence, increase competence. These technologies break down important data streams for businesses and help them understand relevant parameters for achieving desired outcomes. The AI-based IoT solutions help businesses streamline their production-planning process by reducing the expected downtime and identifying and diminish the factors of poor performance.

IoT solutions also help in reducing maintenance visits by describing the accurate and real-time status of machine health. These technologies create large amounts of data. But storing and analyzing these data when needed is a whole different task. For this, companies need Edge AI. Edge AI helps businesses find their point of error and failure in the process.

The Edge in Edge AI technology is used relatively. It helps differentiate the local from the central. However, there is a need to differentiate various types of things that lie at the edge. Employing Edge AI technologies smartly by mapping out clear processes and action plans to achieve measurable results can help businesses deliver better outcomes.

For achieving their business values through AI at the Edge technologies, companies are looking for experts with comprehensive knowledge and skills in this domain to help them implement it in their business models. Considering the rising demands of expertise in this field, Artificial intelligence and machine learning courses are being developed for prospects looking to make a career in this field. Edge AI is entering into every industry slowly and with its enormous potential, it is likely to prove quite beneficial.

TOP 10 APPLICATIONS OF DEEP LEARNING ARTIFICIAL INTELLIGENCE IN DIVERSE INDUSTRIES

Posted on September 10, 2021March 22, 2024 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

Imarticus 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.

How are Analytics and Supply Chain Management Shaping New-Age Careers?

Posted on September 10, 2021March 22, 2024 by Imarticus Learning

Analytics is a relatively new term, but it has already become an indispensable part of our lives. This can be seen in the rise to the prominence of data scientists responsible for gathering & analyzing vast amounts of data from various sources. Data scientists have been instrumental in shaping how companies do business and creating tools that help them explore their data.

Analytics and Supply Chain Management: The Conjunction

Analytics and Supply Chain Management are two areas that have seen a significant transformation in the last few years. Analytics is now being used to improve customer experience, which has become one of the most important goals for businesses.

Supply Chain Management training is being used to increase efficiency throughout the entire supply chain, from production to delivery.

The role these two departments play in business cannot be understated- it’s more evident than ever that they are shaping new-age careers!

How has analytics become an integral part of supply chain management?

Supply chain analytics is the process used by organizations to gain insight & extract data associated with procurement, processing, and distribution. Supply chain analytics is an essential part of SCM.

The mathematical models, data infrastructure, & applications supporting analytics have evolved significantly. This improvement came from better statistical techniques, predictive modeling & machine learning.

Data infrastructure has changed with cloud infrastructure, complex event processing & IoT. Applications now provide insights across traditional application silos such as ERP, warehouse management, logistics & enterprise asset management.

Features of Supply Chain Analytics:

Data visualization: The ability to derive and reciprocate data to have better insights.

Stream processing: Deriving insights from wide data streams

generated by IoT, applications, weather reports & third-party data.

Social Media integration: Using data from social feeds to improve planning.

Natural Language Processing: Extracting & organizing unstructured data in documents, news sources & data feeds.

Location intelligence: Extracting insights from data to understand and optimize distribution.

A digital twin of the supply chain: Organizing data into a comprehensive model of a supply chain can aid in improving predictive & prescriptive analytics.

Supply Chain Analytics Uses

Identifying and improving risks & predicting future threats based on patterns & trends throughout the supply chain.
Boost planning accuracy by analyzing customer data to identify factors that increase or decrease demand.
Improve order management by consolidating data sources to assess inventory levels, predict demand & identify fulfillment issues.
Streamline procurement by organizing & analyzing cash flow across departments to improve negotiations & identify opportunities for discounts or alternative sources.
Increase working capital by refining models to determine inventory levels needed to ensure service goals with minimum means.

Learn and Grow with Imarticus Learning:

If you are looking for a career that has both excellent prospects and flexibility, then, IIT Supply chain Management course offered by Imarticus Learning is perfect for you.

Supply Chain Analytics enables management to make data-driven decisions at strategic, operational, and tactical levels. With this course, you can explore employment opportunities in job roles like Demand Planner, Data Scientist, Supply Planner, and Supply and Operations Planner. Master your SCM skills with analytics through this cutting-edge curriculum that helps you get more data-centric & improve the decision-making of a Supply Chain by leveraging the power of Python.

Can’t wait to Enrol? For further details, contact us through the Live Chat Support system or visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Hyderabad, Delhi, and Gurgaon.

Some Supply Chain Management Trends that’ll Shape the Sector Sharply in Future!

Posted on September 10, 2021March 22, 2024 by Imarticus Learning

Supply chain management has become increasingly important with globalization, as companies have found it necessary to learn more about their supply chains to understand which materials are needed for production or distribution.

Supply chain management: Definition

Supply chain management is a process that deals with the flow of materials, goods, and related information between suppliers, manufacturers, distributors, and customers. It incorporates many different aspects which are constantly changing due to technological breakthroughs.

Supply Chain Trends: An Overview

The Supply chain management sector has evolved over the years. SCM professionals increasingly find themselves having to contend with several challenges such as increased competition for resources, new technologies, and changing customer expectations. A survey named “Improve the Supply Chain with Advanced Analytics and AI “by Gartner elaborate how 96% of supply chain leaders use predictive analytics, 85% use prescriptive analytics, and 64% use AI/ML.

Some Trends in SCM:

Artificial intelligence and machine learning

AIML is at the forefront as a solution to supply chain partners. Be it in-demand forecasting, production planning, or predictive maintenance, AIML is turning is a game-changer. It tracks historical shipment data & converts it into a forecast to gauge seasonal fluctuations in demand & make predictions at a store, product, or facility level. Knowing future needs allows businesses to plan production & predictive maintenance better than ever before.

Internet of Things

Devices communicating amongst them make information flow smoothly and efficiently, operating the whole network. Advanced robotics with big data gives organizations a comprehensive & accurate view of the real-time status of supply chain partners, shipments, and networks. With IoT connectivity comes data that allows highly optimized processes.

Continuous monitoring of critical equipment, improved inventory practices, and increased transparency are other benefits of IoT.

Blockchain

A robust supply chain consists of a known & trusted network. Blockchain technology in SCM can counter many related challenges. Entities in the blockchain network can track where the transaction originated from. Be it raw materials, payments to vendors, or copyrights of assets, everything is in a loop. Since deletion of trade within a blockchain is impossible, it adds to the transparency of transactions, ensuring the security of the entire operation.

Advanced analytics

Advanced analytics allows organizations to work with processes in real-time. In-depth analytics let professionals extrapolate data from existing conditions & imagine future scenarios to design more profitable strategies & create an efficient supply chain. The ability to track orders, optimize transportation, & even analyze returns on products & routes make it essential to integrate advanced analytics into SCM platforms.

Custom applications

Most new-age companies need unique solutions to cater to specific requirements of business & inter-departmental needs. Custom applications are personalized that enables management to gain greater power with real-time visibility, flexibility on move, dynamic tracking, increased

collaboration & hands-free operations. By leveraging these technologies, professionals can ensure that businesses survive but thrive in this chaotic environment.

Make a Career in SCM with Imarticus Learning!

Future-proof your career with a supply chain management course from Imarticus Learning. The supply chain certification online course equips students to make data-driven decisions at strategic, operational, and tactical levels.

Due to the shortage of professionals with process and analytics talents in SCM, this program prepares students for high-demand job roles like Demand Planner, Data Scientist, Supply Planner, and Supply and Operations Planner.

Uniquely designed by IIT faculty & industry leaders, this 6-months program prepares you to gain the best from this opportunity.

Contact us through the Live Chat Support system or visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Hyderabad, Delhi, Gurgaon & Ahmedabad.

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

Posted on September 9, 2021March 22, 2024 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

Imarticus 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.

Why Is It So Easy To Get an Analytics & AI Certification, But a Struggle To Get The Right Job Interview Opportunities ? Imarticus Has an Answer

Posted on September 8, 2021April 4, 2024 by Imarticus Learning

The data science domain is expanding. With it, the demand for AI, ML, NLP, and other data science careers is also rising. Reports suggest that there were 2.9 million data science job openings in 2019 alone and by 2026, this number is going to go up to 11.5 million.

Despite this huge demand, getting a good job in the AI and Analytics field is a real struggle. Many aspiring people do many courses in different branches, be it computer visions or deep learning. But when it comes to securing a job, a lot of them find it extremely difficult.

Key Reason for Difficulty in Job Seeking

While most of the people blame it on the companies that they don’t understand what they want, the harsh reality is that most of the aspirants in this sector lack the important skills required to get a good job interview opportunities. Many candidates are not competent enough to grab a job role in data analytics or the AI field. Data science is a complex field that requires an extensive amount of knowledge and a high-level skill-set.

Though many students do certificate courses from various institutions online, most of the time they do not get taught and trained the right way. It results in students missing out on important concepts, analytics, and numerical aptitude. When these students go out in the real world, they end up facing rejection on their job applications.

The thing is if students want to build careers in the data science field, they need to be exceptionally well at it. For this, they need to pursue a course that builds their foundational and advanced knowledge in-depth and provides them with the crucial practical skills required in the real world.

Imarticus Learning PGA – The right way

Imarticus Learning offers a Post Graduate Program in Analytics & Artificial Intelligence that teaches the in-demand tech skills in the job market at present. The teaching method involves engaging videos, live sessions, and exercises.

Industry professionals having years of experience in this field deliver ML, computer visions, and deep learning training projects.

Upon completion of the post-graduate program in data analytics course, Not only but students also get guaranteed job interview opportunities and placements in leading companies.

The PGA course covers theory and practical learning on the following subjects:

Data Science Fundamentals
Deep Learning
Machine Learning
Computer Visions
Natural Language Processing
Placement Preparation

During the entire duration of the course, students are provided with a mentor who supports them in their academic journey and guides them in their career path. The mentor performs the following roles:

Motivate and Inspire to engage in projects and their completion.
Monitor your grades and potential.
Build meaningful connections that will help you beyond the course.

By studying the PGA course with Imarticus Learning, students get complete support and guidance throughout their learning process. The career services provided with this course include:

Guaranteed Jobs
Resume Building
Interview Preparation
Profile Enhancement

Job Roles after PGA Course

Upon successful completion of the Imarticus Learning PGA course, you can find suitable careers in:

Business Analyst
Artificial Intelligence Engineer
Data Analyst
Machine Learning Engineer
Data Science/Machine Learning Consultant
Web & Social Media Analyst
Machine Learning Architect
Data Scientist

The salary packages in these job roles are quite lucrative. The average pay scale in Analytics & AI roles is around INR 5 LPA to 25 LPA.

Joining Procedure of PGA Course

Candidates interested in Analytics & Artificial Intelligence can join this program for building a successful career in this field. The joining procedure is simple and includes three steps:

Detailed Profile Check
Online Tests
Enroll

The prerequisites for the course include a graduation degree with a minimum of 60% and a basic understanding of mathematics and programming. With data analytics course, students can get the best education and make their dream of becoming a professional in this field come true.

How Can Computer Vision Protect Millions of Homes From Intrusion?

Posted on September 8, 2021March 22, 2024 by Imarticus Learning

Introduction

We need to embrace the concept of computer vision in homes rather than shy away from the idea of exchanging personal data to achieve new levels of protection, safety, comfort, and entertainment. Computer vision combined with NLP and ML enables computers/systems via digital images or video to understand what they see.

When systems can detect and recognize objects, according to what they are scheduled to do, they can deliver intelligent behavior. Automotive space is one area that has successfully demonstrated how computer vision can change our lives. Car systems that use computer vision can recognize the driver behind the wheel and can warn the driver when he starts to swerve out of his lane to see the surrounding area.

Many customers on their smartphones are already using computer vision and don’t even know it. To recognize facial features and position overlays (philters) in the right positions, both Snapchat and Instagram use computer vision tracking.

How does Computer Vision help us in making things secure?

Accepting computer vision into your house and connecting it to your connected devices helps your daily routine to have a new level of convenience. When you arrive and open the door for someone, the front door will be able to see or stay locked when an unknown person (face) approaches. Alarm systems are smarter, able to distinguish who are family members (including age and gender) and who are not.

If an elderly family member or visitor trips, or if a child is climbing up the stairs, on the countertop, or anywhere that puts the child in danger, indoor surveillance cameras will send a warning to your mobile, taking it a step further. Nest, Logitech, and other smart home manufacturers have either begun offering customers these smart security features as a premium subscription service or have already incorporated them into their newest devices.

Computer Vision in Intrusion Detection

Abbreviated as IDS, an Intrusion Detection system plays an important role in providing the required security assurances for all networks and information systems in the world. One of the solutions used to decrease malicious attacks is IDS. As attackers often change their attack tactics and find new methods of attack, IDS must also develop by implementing more sophisticated detection methods in response.

The enormous data growth and substantial developments in computer hardware technology have led to the existence of new studies in the field of deep learning, including intrusion detection.

To provide a high degree of security and security staff monitoring effectiveness, high-performance AI systems can make the task monitoring process automatic for high-risk sites. Also, these intrusion systems can identify objects based on size and location. However, they fail to recognize the type or form of the detected object.

Perimeter Defense (Intrusion Detection) systems with high-end artificial AI algorithms to identify a multitude of different types of objects can now discern objects of interest, thus dramatically reducing the rate of such intrusions that might indicate a false alarm. The more sophisticated systems, such as those provided at IronYun, allow its customers to design ROIs based on intrusion detected points, high-value areas, and or any other region that may be beneficial for alerts.

Similarly, the applications designed for face and license plate recognition have the ability to detect people or cars(the license plate) in addition to solutions for motion detection and use pre-designed data to identify distinct faces or plates that should be watched regularly, similar to the pre-designed lists.

Needless to say that these systems will also allow its customers to search for faces that are not provided already on the camera. For example, if a person is identified hanging outside a house many times, one can store their pictures in the designed watchlist and fix an alarm when the face is identified again around the house or in your surroundings.

The main advantage of the system is that before the troublemaker completes the act, the warnings will assist in discouraging and avoiding vandalism or robbery and inform the authorities of the scene.

Conclusion

AI-based security measures combined with computer vision, deep learning, ML, and NLP training can do all the boring work for you to help deter fraud and vandalism. They are also the most accessible security solutions available with a strong return on investment due to their low cost and outstanding reliability.

Stopping crime is a challenging, ongoing challenge, but enterprise vendors and law enforcement can do it more easily with the right AI apps. This is also one of the reasons why people are excited about an acceptable career in the AI sector.

AI and ML are Enhancing Marketing and Sales Strategies across Industries

Posted on September 8, 2021March 22, 2024 by Imarticus Learning

Understanding the AI & ML Technology

Artificial Intelligence (AI) technology has revolutionized the way businesses function and operate. It has given a massive push to businesses by leveraging big data and smart analytics. Artificial intelligence technology is a broad discipline related to computer science that helps to develop smart machines/systems that are capable of performing complex tasks that earlier needed human intervention. Simply put, artificial intelligence technology helps to simulate human intelligence into machines that can learn to perform tasks using their intellect.

Machine Learning (ML) is a branch of artificial intelligence technology that deals with the process of training machines through using complex data sets. It helps machines to acquire the knowledge needed to perform a certain task using tons of data for every particular scenario.

It can be understood as an application of artificial intelligence technology that imparts machines with the ability to learn from their past data processing experience. Machines use their learning to process data based on real-time inputs.

Artificial intelligence and Machine Learning career is considered as one of the most sought after ones in the contemporary given its demand in the industry.

AI & ML Alleviating the Marketing & Sales Experience

In the contemporary digital era, people are more accustomed to buying things online. This has created new opportunities for organizations to leverage technology into their sales and marketing endeavors. Digital marketing has helped companies to reach their targeted customers easily and it has also boosted the conversion rates.

Today, marketing is all about understanding your customers and offering them what they really want instead of just blindly pushing products. It requires understanding consumer behaviour, interest, purchase patterns, etc.

Brands deploy AI & ML algorithms to personalize the shopping experience for the customers by leveraging big data that provides them with actionable insights. AI-powered tools have drastically enhanced the marketing game and help to maximize returns on the marketing expenditure. Better consumer targeting also helps to increase the conversion rates and a personalized shopping experience helps to boost customer satisfaction. This aids to increases the top line of the companies easily.

Artificial intelligence technology along with advanced analytics tools have proved to be a boon for businesses when it comes to complementing marketing and sales efforts. It helps to provide useful actionable insights by assessing tons of user data and providing better information that allows effective targeting.

It is almost impossible to flawlessly analyze such high volumes of data on a daily basis using human labor. This is where artificial intelligence and machine learning technologies come as a helping hand. AI tools help to process large volumes of data in a fraction of seconds and also predict the future trends that might be helpful for the business.

Conclusion

AI & ML technology along with advanced analytics has revamped the marketing and sales landscape by providing valuable insights into useful data and fast data processing experience. Artificial intelligence career is also growing popular and one can learn more about this discipline by opting for an artificial intelligence and machine learning course by reputed institutions like Imarticus Learning that provides you with a comprehensive understanding and placement assistance with the most reputed firms in the industry.

How To Create An Image Dataset and Labelling By Web Scraping?

Posted on September 8, 2021December 5, 2023 by Imarticus Learning

Every data science project starts with data. We need to acquire a huge amount of data to train our machine learning models. There are various ways to collect data. Surfing websites and downloading the structured datasets present on them is one of the most common methods for data collection. But there are times when this data is not enough. Certain problem statement datasets are not easily available on the web. And to deal with this situation, we need to create our own datasets.

In this article, we will discuss the method of creating a custom image dataset and labeling it using Python. First, let us talk about acquiring images through web scraping.

Web Scrapping

Web Scraping refers to the process of data scraping from websites. It surfs the world wide web and stores the extracted data in the system. Beautifulsoup is one of the most popular Python libraries for image scraping. The requests library requests the essential webpage.

How To:

When we go to the developer tool by clicking on a picture on the webpage, there displays a format starting with images.pexel.com/photos after which a number is listed, which is unique for every photo. One can get a similar image using the regex (regular expression).

Using this method, our images get scrapped. We can also print the links if we want to see those links and make a directory of them. After this, we will download the images. Once the process is complete, you can see the scrapped images through the specified path where images are stored.

Labeling

After scrapping and storing the images, we need to classify them through labeling. Labeling software is used for this purpose. It is a pip installable annotation tool. It provides two annotations YOLO and PASCAL VOC.

How To:

You can open the labeling software using the command: (base) C:\Users\Jayita\labeling

There will be specified options on the left-hand side of the screen. On the right-hand side, you will see the image file information. Select ‘Open dir’ to see all images. Press ‘a’ to view the previous image and ‘d’ to view the next image.

To get the annotations, draw a rectangular box and press ‘w’. A window will pop up to store the image’s class name. Once you are done with drawing the box and labeling the image, it’s time to save it. To generate the annotations, you need to store the image in PASCAL VOC or YOLO format.

One can learn about this in detail in a data science course. Web scrapping and labeling is not a hard process once you understand the basics of it. You need to be careful while scrapping a website and obey the rules so that you do not harm the website you are scrapping. Take time to consider your requirements and research accordingly to find a suitable website for this process. For example, if you plan to develop a model for fashion, then online shopping websites should be on your scrapping list.

Learning web scraping and labeling is important if you want to build a data science career in the future. It will provide you with a deep understanding of image datasets. You can use these techniques to increase the data in situations where available data for a project is less. You can apply this process to multiple classes if they share the same folder and get the desired results.