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Tag: Machine Learning Online Training

How Artificial Intelligence Training Helps to Boost The Fashion and Advertising Agencies?

Posted on by Imarticus Learning

In a fast progressing world such as ours, the need for an efficient tool to speed up the process of our work has increased. With that demand came the answer to all our problems, Artificial intelligence (also known as AI).

At this moment in time AI is being used across almost all major industries. A large number of establishments not using AI face being left behind in our extremely competitive economic race.

In this article, we will be shedding light on its advantages in the fashion and advertising industries.

AI and the fashion industry:

AI has established its role in the fashion industry quite firmly. Fashion retailers are going bankrupt due to the lack of importance given to AI. Due to this high demand, each year, the total expenditure on AI in the fashion industry is estimated to reach a whopping $7.3 billion by the end of 2020.

In the fashion industry, where only the top 20% of global brands are considered to be profitable, the need for a tool to maintain their relevancy is immense. It allows easy access to large chunks of data, customer personalization, and various other services which the fashion companies will not be feasible to run without.

AI is used mainly in three areas:

  1. Apparel design: Due to its ability to collect intricately detailed data sets, fashion companies are using this technology to better satisfy and understand customer needs and also be able to design better clothing from feedback. Zalando which is a German-based fashion platform has been designing its clothes using AI which picks up information depending on a wide set of customer choices which range from the material of clothing to clothing style and color.
  2. Making manufacturing easy: Fashion trends are fast-changing and there is a need for the pattern of change to be identified. AI is able to do this with ease while also being able to supply the apparel to shelves much faster than a normal retailer. Taking advantage of this, companies can confidently provide immediate service thus gratifying their customers based on their demands and needs. Examples of companies using this are brands such as Zara, TopShop, and H&M.
  3. Selling merchandise virtually: AI has the ability to break down the walls between the online and in-store shopping experience. This is being done through augmented and virtual reality technology, allowing customers to access apparel online using AR. Certain brands like Tommy Hilfiger are using virtual reality to create virtual pop-up retail stores.

Now you may ask how this works. AI is largely used in the fashion industry in the form of chatbots using which the fashion brand gathers information about the customer’s needs and desires. It has become an indispensable tool and is able to identify the customers fast changing desires.

AI and the Advertising industry:

AI plays a very important role in the advertising industry as well. It is able to identify elements that will resonate with the viewers, creating ads without any human involvement. It is also able to perform audience targeting and ad buying. Major platforms are using AI, taking advantage of its ability to determine if viewers would click on the ad they are being presented with.

It is able to intelligently identify and segment audiences, build ad creative, test variations, improve performance and also optimize spend. It has proven to be advantageous to digital advertising and the careers of marketing experts who plan and run ad companies.

Advertising at scale is something that is tricky and impossible for humans to perform and AI comes in quite handy here. The technology has the unique ability to detect patterns and predict what changes need to be made to a campaign to improve it against its specific KPI. This does not take days, hours, or even minutes but can be done in a span of just a few seconds.

The advantages of AI in advertising are hence as follows:

  1.  Increasing revenue through analyzing data at scale
  2. Reducing costs by acting on data faster and automatically
  3. Creating a massive competitive advantage

It plays a key role in real-time advertising, buying, and selling. This is most popularly done with the help of third-party apps like Facebook, Instagram, and Snapchat. These ads are suggested through AI looking at the links that are promoted by the user.

Taking all these facts into consideration it is pretty clear that a career in AI, especially in our day and age has huge scope and its benefits are undeniable! AI is transforming the fashion and the advertising industry as well as many other industries and thus considering artificial intelligence training at this point is a very smart thing to do!

Certification in Artificial Intelligence and Machine Learning in Collaboration with E & ICT Academy, IIT Guhawati, and Imarticus Learning

Posted on by Imarticus Learning

Machine learning is powered by AI. With ML, we can power programs that are easily updated and modified to adapt to new environments and tasks- resulting in quick progress on difficult projects. ML and AI are almost synonymously used in tandem when it comes to the latest tech trends. And, AI has disrupted many industries forever – like SaaS, Manufacturing, Defense, Analytics, public sector, and so on.

If you learn machine learning through the best Machine Learning & AI course, you are likely on a fast and high-growth career trajectory.

Here is why!

#1. ML & AI Are Skills of the Future

Skills in ML can affect your long-term employment prospects because the field is projected to experience rapid growth.

With the emergence of advanced technologies like the Internet of Things (IoT), Machine Learning is experiencing a certain surge in demand and popularity.

If you learn machine learning by taking up data science certifications, there is an increase in the probability that you will have better job prospects as compared to someone without ML skills.

#2. Solve Real-World Problems

There is a lot of talk about how AI will replace jobs, but the truth is it will create new job opportunities. As an ML engineer, for instance, you get to work on projects that have a big impact in the real world and lead to business solutions that are meaningful.

#3. Versatile Growth Opportunities in the Data Sciences

Machine learning and artificial intelligence (ML &AI) skills are beneficial to a data science career. Both positions give you the opportunity to let your knowledge of both fields expand. Switching back and forth between roles can quickly enable you to become an invaluable resource in today’s rapidly changing world.

You want to have an advantage as early as possible so that you can learn about solving new and undiscovered problems. When the time comes, these skills will be in great demand and allow you to secure a career path on the rise.

What does a growth path in this domain look like?

Typically, a machine learning engineering career path begins with being a Machine Learning engineer. Machine learning engineers develop applications that automate common tasks previously done by humans and take care of the repetitive ones for humans to do efficiently without error.

When you earn a promotion as an ML engineer, you are then promoted to be an ML architect! Their responsibility is developing and designing prototypes for applications that need development.

There are a few other roles in the field which one could take on as well. These include ML data scientists, ML software engineers, senior software architects, and more.

New tech arenas keep developing into this space. So, keep your interest, skills, and industry demands aligned for the best growth!

How to make a successful career in AI & ML?

Want to learn machine learning with the best Machine Learning & AI course?

certification in Artificial Intelligence and Machine Learning

Imarticus brings to you the class-leading AI & ML certification in collaboration with E&ICT Academy of IIT-Guwahati.

Our highly-rated program has fostered hundreds of successful professionals serving the industry worldwide. Your chance to be a part of this prestigious career trek begins with us.

Enroll with Imarticus now!

Jobs of The Future: Artificial Intelligence and Machine Learning

Posted on by Imarticus Learning

COVID-19 has inverted the ways we lived. The jolts can be felt across workplaces, particularly where it has forced organizations to reduce activities, including leisure, restaurants, oil & gas, and airlines. Throughout COVID-19, the technology industry remains strong. The pandemic spurred technological innovation and enabled many to continue work despite lockdowns & other pandemic mitigation measures.

Benefits of AI?

  • Automation: AI gives a better understanding of machines to interpret a situation or perform necessary action. Tasks can be automated with minor human intervention through AI/ML. While automation takes place, the roles requiring human attention automatically become more productive with more time to focus on them.
  • Speed: AI is efficient in expediting much work when compared to humans. AI lets us complete tasks flexibly before deadlines. This reduces human labor & provides great speed & efficiency.
  • Accuracy: AI eliminates maximum chances of error. The machine always acts according to a fixed AI algorithm; there are fewer errors in every given scenario. In short, AI defines new limits of accuracy & precision with lesser risks.
  • Exploration: AI has helped to discover many new sites, for example, volcanic sites, ocean beds, etc. Humans being vulnerable to these sites, can’t reach and survive these scenarios. Robots are meant to go to these places and collect data.
  • Data Collection & Analysis: Data analytics is the future technology in today’s business world. Industries & businesses analyze valuable chunks of data & extract helpful information.

Applications of AI?

Artificial Intelligence and Machine Learning courses in IndiaAI is applicable in every conceivable field & recent advancements are increasing the relevance of AI in every sphere. Here are the top applications of AI:

  • Speech Recognition: AI allows us to convert spoken words into digital content. Speech recognition has various uses like voice-enabled messaging, content writing, voice-controlled remotes, & appliances. Speech recognition is also used for authorization & validation.
  • Natural Language Processing: NLP enables a machine to understand the human text. Virtual assistants like Siri, Google Assistant, Alexa, are all an example of chatbots working on the principle of NLP.
  • Stock Trading: There are AI platforms that allow automated stock trading. With the algorithms, these bots understand the fluctuations in the stock market & predict high-return stocks with more accuracy. The future scope of AI/ML in the finance sector is fuelled up due to the increasing craze for cryptocurrency.
  • Robots: Besides developing intelligent robots, AI has created robots that assist humans with routine tasks like cleaning, gardening, serving, etc.

Explore Careers in Artificial Intelligence with Imarticus Learning:

Freshers need to realize their competencies & acquire skills for AI roles with chances of upward mobility in career. The future scope of Artificial Intelligence is increasing due to new job roles & advancements in the AI sector. 42% of the IT workforce in India will require upskilling or reskilling by 2025. Imarticus Learning offers artificial intelligence and machine learning courses and machine learning certification courses to upskilling & and stay relevant.

The program builds a strong foundation of Data Science concepts. Industry experts will help you learn the practical implementation of Machine Learning, Deep Learning, and AI techniques through real-world projects from diverse industries. The 9-month extensive program will help you prepare for the Data Analyst, Data Scientist, Machine Learning Engineer, and AI Engineer roles.

This state-of-the-art Artificial Intelligence and Machine Learning Certification Course aim to let students learn machine learning & prepare for future jobs.

For further details, contact us through the Live Chat Support system or visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Hyderabad, Delhi, Gurgaon, and Ahmedabad.

How Can AI Help to Enhance Conversational Business Intelligence?

Posted on by Imarticus Learning

Data, Analytics, Insights are the three key terms connected with the success of any organization. Well-curated and holistic customer data can take businesses to a whole new level.

It is the Business Intelligence Dashboard that keeps a record of KPIs, metrics, and various other data related to the organization, departments, or a specific process. While Business Intelligence Dashboards can provide a whole lot of information, it may require a considerable amount of time and effort to access the data.

Consider a scenario where a manager needs the sales of the Southern Territory for the past quarter. He also needs the list of jobs currently running on the organization’s server for new recruitments. All the information he needs will be available in the organizational Business Intelligence dashboard. But to access the specific data, he has to undergo several processes.

He has to log in for each task, set the parameters, range, format, etc, which is time-consuming and also tedious. This is where the AI-enhanced Conversational Business Intelligence comes in handy.

In today’s dynamic and competitive market, Conversational Business Intelligence powered by Artificial Intelligence has a unique role. It helps the organization to improve customer experience, involves minimal business decision-making, and also helps in offering more personalized services. It provides a whole new approach to your daily business tasks.

AI-enhanced Conversational Business Intelligence is an intelligent interface between the dashboards and the users. It not only helps in gathering the specific information at a rapid speed but makes use of a structured and user-friendly format to present the data.

It delivers quick and exact responses. Conversational Business Intelligence is beneficial both at the customer end and also for the employees within the organization. It helps to receive crucial data and insights about the customers by simplifying and speeding up the entire process.

The employees can access data without worrying about extra passwords, another application, or new software. Conversational Business Intelligence enhanced by Artificial Intelligent is easy to collaborate with any platform of your choice.

Let’s look at another instance where Artificial Intelligence enhanced conversational business intelligence comes to your help. Using Google Analytics, you get valuable insights related to your customers such as what page they are viewing or how frequently they have visited a page of your site, etc.

But what it does not answer is WHY that specific customer revisits a page, the pricing page for instance, and does not continue with the purchase or opt for a trial option as mentioned on the page.

There could be several reasons stopping the customer from making the purchase. He could be hesitating because the page does not provide enough details to convince him, or he could be confused about the purpose of the product, or he could be worried about the delivery of the product, etc. However, the reasons are unknown.

This is where the AI-enhanced conversational business intelligence comes to your rescue. The customer can now communicate their problems, to a system mimicking human intelligence, without actually having to talk to the manager or owner of the site in person and can clarify all his doubts regarding the specific product or page instantly.

Why a career in Artificial Intelligence?

Artificial Intelligence trainingArtificial Intelligence in Business Intelligence makes use of computer systems to mimic the various abilities of human intelligence such as reasoning, learning, understanding, communication, perception, judgment, and much more.

With the fast-growing businesses and a huge number of customers, the data generated today is much more than what one can absorb or interpret.

With this kind of data, it can get really difficult for human minds to make complex decisions. This is why Artificial Intelligence is said to be the future of all complex decision-making. Therefore, an Artificial Intelligence career can provide endless job opportunities.

The Art of Machine Learning!

Posted on by Imarticus Learning

Machine learning is the application of Artificial Intelligence (AI) that enables systems to learn automatically and improve from experience without being programmed directly. Its main focus is on the development of programs that access data and use the same for self-improvement.

The machine learning process starts with observing data to look for similar patterns in any form and make better decisions in the future based on these trends. The main aim is to enable the computers to learn automatically and adjust actions accordingly without human intervention or assistance.

Data mining and predictive modeling involve similar processes as machine learning. Both these methods involve searching through data to look for patterns and then adjusting the program actions according to those patterns.

A common example of machine learning for people is shopping on the internet and being served ads related to it. This happens because online ad delivery is personalized almost in real-time by recommendation engines using machine learning.

Along with personalized marketing; detection of fraud, spam filtering, network security threat detection, predictive maintenance, and building news feeds are other common machine learning use cases.

Some machine learning methods
Machine learning algorithms are often categorized as supervised or unsupervised.

  • Supervised machine learning algorithms can apply past learnings to new data with the use of labeled examples to predict future events. It starts with the analysis of a known training dataset based on which the learning algorithm produces an inferred function to make predictions about the output values.Targets are provided by the system for any new input after sufficient training. The learning algorithm can also compare its output with the correct, intended output and find errors in order to modify the model accordingly.
  • Unsupervised machine learning algorithms – These types of algorithms are used when the information used to train is neither classified nor labeled. Unsupervised machine learning enables you to understand how systems can infer a function to describe a hidden structure from unlabeled data. The output given by the system is not right, but it explores the data and can draw conclusions from datasets to describe hidden structures from unlabeled data.
  • Semi-supervised machine learning algorithms have qualities of both supervised and unsupervised learning since they use both labeled and unlabeled data for training. Mostly, these algorithms use a small amount of labeled data and a large amount of unlabeled data. Learning accuracy is considerably improves in systems using this method.When the acquired labeled data requires skilled and relevant resources in order to train it or learn from it, semi-supervised machine learning is used. Otherwise, additional resources are generally not required for acquiring unlabeled data.
  • Reinforcement machine learning algorithms is a learning method that collaborated with its environment by delivering actions and finds errors or rewards. The most pertinent characteristics of reinforcement learning are trial and error search and delayed reward.Machines and software agents can automatically determine the ideal behavior within a particular context in order to maximize their performance using this method of machine learning. Simple reward feedback is required for the software specialist to learn which action is best and is known as the reinforcement signal.

Large quantities of data can be analyzed using machine learning. It identifies profitable opportunities or dangerous risks by delivering faster, more accurate results; however, it may also require additional time and resources to train it properly.

Large volumes of information can be processed more effectively if machine learning is combined with AI and cognitive technologies.

For example, Facebook’s News Feed customizes each user’s feed with the help of machine learning. If a user frequently likes or shows any activity on a particular friend’s posts, the News Feed will start to show more of that friend’s activity earlier in the user’s feed.

At the backend, the software is simply using statistical analysis and predictive analytics to identify patterns in the user’s data and use those patterns to populate his/her News Feed. If the user no longer shows interest to read, like, or comment on the friend’s posts, that new data will be included in the dataset and the News Feed will update accordingly.