This is a tutorial where we teach you to do image recognition using LSTM. To get to the core you have to understand that how a convolutional neural network perceives the data. In this tutorial the data we have is four-dimensional data, so, you need to convert the dataset accordingly. You can find the tutorial video attached to this blog.
Now suppose there is an image 28 by 28 pixel, if the image is black and white then there would be only one channel. So how will you put the data in CNN, it will be like the number of samples, then followed by the number of rows of the data, then the number of columns, then channels. These are the four values that need to be provided in the input layer, at the very beginning. Now, these values must be converted according to the LSTM. Now the LSTM wants the STF, like the number of samples, time steps like how many time steps back you want to go for making further prediction because LSTM is a sequence generator and the number of features. So, we will be converting the image that is the number of sample 28 by 28 one pixel into one sample of 28 by 28, that’s the only job you have to do and all you need to accomplish this is to prepare the data accordingly.
There will be no mysteries here, in fact, it is a normal neural network LSTM, that anybody can run in a most simple form, and in this tutorial, it is also run in the most simple form there is no complexity involved and only a few epochs will be run.
You can find the code sheet you need for this at
Also follow this video that explains the process step by step, so that you can easily grasp how LSTM can be used for the purpose of image recognition. To access more informative tutorial sessions like this follow the DexLab Analytics blog.
Dexlab Analytics is undoubtedly a leading name in the field of the Big Data Analytics industry. The latest offering from this institute is a course that is remarkable in so many ways. The course is Mega Artificial Intelligence Course In Python, which aims to cover everything you ever need to learn regarding artificial intelligence. To help you get a better grasp of the course we have also prepared an online demo and the demo video is attached at the end of the blog do check that out to clear away any confusion you might have.
Before getting into the course details, there are certain features of the course that we think you should know about. To begin with, you do not need any special educational background, you can hail from any stream and can still pursue the course because here we will teach you from scratch. Just having some mathematical knowledge is fine. We have kept things flexible here, so you can repeat the course if and when necessary. The notes that you will be needing for the course including the code sheets, will be provided to you in the beginning so that you do not have to waste precious time in class taking notes.
However, the nature of the course will be online, because due to COVID 19 situation offline classes are temporarily not possible. You will be given all the classroom videos, furthermore, there will be guidelines regarding Kaggle.com where we will teach you how to participate in this pioneering data science website, how to compete over there and offer you tips to increase your ranking. All in all the course aims to transform you into a super data scientist.
You can find the detailed course information, the online demo and brochure in the PPT format at
The course will be divide into three sections starting with PYTHON PROGRAMMING for Data Science. Throughout the sessions, you will get familiar with the language, its libraries. You will be taught to use Plotly and handle projects before moving onto the second section which is AI( Artificial Intelligence) comprising three components namely Statistics, Machine Learning, and Deep Learning. Along with picking up the nuances, you would handle mega projects including one on self driving cars. Moving on to the next segment of Big Data get introduced to PySpark. Handling a growing amount of data could be tough, so, an introduction to Quantum Computing seems necessary before wrapping things up.
Do check out the course details in the video attached below that gives you a thorough tour of the entire course and also check out the course brochure. Our contact number is provided there along with our website address, feel free to contact us regarding any query.
When you interact with Alexa, or, conduct a voice search on Google, do you wonder about the technology behind it? What is it that makes it possible to communicate with machines as you would with a human being?
Natural Language Processing (NLP) AKA computational linguistics is a subset of Artificial Intelligence, makes all of it possible by combining artificial intelligence, machine learning, and language to facilitate interaction between computers and humans.
So how does NLP work?
When you put a voice command, it gets recorded and then the audio gets converted into text, and the NLP system starts working on the context and the intention of the command. Basically, the words that we speak are labeled and get converted into a set of numbers. However, Human language is complex and has many nuances and underlying subtexts. The same word under a different context can have different connotations. So, when a simple command is put is gets easier for the machine to follow through as it contains simpler words and clear context, but, the system needs to evolve more to fully process the complex language patterns that evolved through ages. There are courses available such as natural language processing course in gurgaon that can help one acquire specialized knowledge in this field.
NLP and its applications
NLP despite being in a nascent stage is getting recognized for its potential and being applied for executing various tasks.
Sentiment Analysis to assess consumer behavior
This functionality of NLP is an important part of social media analytics that parses the comments and reactions of users regarding products, brand messages spread over social media platforms to detect the mood of the person. This helps businesses gauge customers’ behavior and to make necessary modifications accordingly.
Email filtering and weeding out spam
If you are a user of Gmail then you must have noticed the way your emails get segmented once they arrive. Primary, Social, and Promotions are the three broad categories followed by others, there is a segment for spams as well. This smart segmentation is a stark example of NLP at work.
Basically text classification technique is used here to assign a mail to a certain category that is pre-defined. You must have also noticed how well your spam is sorted, this is another result of the application of NLP where certain words trigger the spam alert and the mail gets sent straight to the spam folder. However, this sorting is yet to be perfected via further research.
Automatic summarization to find relevant information
Now thanks to digitization we have to deal with huge amounts of data which has led to information overload. This massive amount of data needs to be processed to find actionable information. Automatic Summarization makes it possible by processing a big document and presenting an accurate and short summary of it.
Chatbots
No discussion on NLP can ever be complete without mentioning the chatbots. The customer service segment is gaining huge benefits from these smart chatbots that can offer virtual assistance to the customers 24×7. Chatbots can not only enhance customer experience but, are also great for reducing costs for any business. However, modern-day chatbots can handle simple, mundane queries that do not require any special knowledge and skill, in the future we could hope to see the bots handling specialized queries in real-time.
Spell and grammar checker
If you have ever used Grammarly and felt impressed with the result then you must have wondered at some point how does it do it? When you put in a text, it not only looks for punctuations but also points out spelling errors and also shows grammatical errors in places where there is no subject-verb agreement. In fact, you also get alternative suggestions to improve your writing. All of this is possible thanks to transformers used by NLP.
Machine Translation
If you are familiar with Google and its myriad apps then you must be familiar with Google Translate. How quickly it translates your sentences in a preferred language format, machine translation is one application of NLP that is transforming the world. We always talk about big data but making it accessible to people scattered across the globe divided by language barriers could be a big problem. So, the NLP enabled us with machine translation that uses the power of smart algorithms to translate without the need of any human supervision or intervention. However, there is still huge room for improvement as languages are full of nuanced meanings that only a human is capable of understanding.
What are some examples of NLP at work?
We are not including Siri, or, Alexa here as you are already familiar with them
SignAll is an excellent NLP powered tool that is used for converting sign language into text.
Nina is a virtual assistant that deals with banking queries of customers.
Translation gets easier with another tool called Lilt that can integrate with other platforms as well.
HubSpot integrated the autocorrect feature into its site search function to make searching hassle-free for users.
MarketMuse helps writers create content that is high-quality and most importantly relevant.
Just like AI and its various subsets, NLP is also a field that is still evolving and has a long journey ahead. Language processing is a function that needs more research because simulating human interaction is one thing and processing languages that are so nuanced is not a cakewalk. However, there are plenty of good career opportunities available and undergoing an artificial intelligence course in delhi would be a sound career move.
Running a business is a challenging job, especially when business operations take place on a small-scale platform. Small business owners need constant motivation and brainstorming to keep their business in a profitable position.
However, as the world is busy deriving benefits from AI technology, and professionals opting for artificial intelligence course in delhi for better career prospects, small business owners too should seize this opportunity to power up their businesses.
Why the small business owners are shying away from AI?
With biggies like Google, Amazon, Apple, Microsoft empowering themselves with AI tools, small businesses are somewhat showing reluctance towards the new technology. Only a small percentage of businesses ranging from small to medium have so far been influenced by it. A 2018 survey showed the number to be around 13.6%.
This indicates there is some inhibition in the small business community, but, it might not just be that, when questioned most small business owners often cite reasons like lack of expertise, financial concern to be the causes.
They are mostly under the misconception that such advanced technology is best suited for giant platforms and their small scale businesses are not going to rake in any profit, even if they invest. They don’t even have tons of data like most businesses, to begin with. So, AI being a data-driven technology, might not work for them.
Their perception is gradually changing because of the way AI has started seeping through the very fiber of civilization and impacting so many aspects of life. It is not possible for small businesses to indulge in AI research or, develop a platform specifically for their business needs for feasible reasons but, they can get ideas regarding how best to conduct business the AI way.
Let’s find out how AI can be incorporated into small business infrastructure to improve five core areas.
Smarter sales and marketing with AI-powered CRMs
A CRM is an indispensable tool for any business, let alone a small one. Basically, a CRM works to garner customer data from various platforms to enable the sales and marketing team to keep track of their valuable customers while pursuing new leads.
The fusion of AI and CRM could do wonders as it is evident from the way Einstein AI, introduced by SalesForce is working.
You stand to gain insight into the customer mindset as this fusion will work to analyze customer mindset by analyzing the conversations that happened across different channels. This insight can help shape your sales and marketing efforts accordingly especially if you can upskill your team with customer market analysis courses.
Keep an eye on your rivals
Staying one step ahead of your biggest competition in the market is a crucial need no business owner big or small can afford to ignore. However, it is not easy to monitor every move they make, but, AI can be your biggest ally in helping you track your rival’s every digital move.
AI-powered Crayon, is a smart tool that monitors what your competition is doing on social media, across websites and applications, you can gauge their performance and activities and keep a tab on their marketing strategies, pricing, and other such issues to make suitable modifications to your own.
Automate customer service
Handling your customers is an important but, tedious task and as your business starts to grow so does your customer base and their queries. Investing in a big support team might not always be a feasible option for you, so why don’t you take advantage of chatbots to automate the whole process and make it more efficient?
Not all queries are important, some of these are generic which the chatbots can handle while your sales team can focus on more personalized or, technical queries to keep your customers happy. Answering support tickets can be easy with a tool like Digital Genius. It is a great option even for those businesses which can’t afford a support team.
Smoother HR operations
No matter how small scale your business might be, you still have to manage your employees and hire new ones, which means having an HR team ready round the clock. Now you can manage this segment bypassing all hassles thanks to AI-powered platforms that automate your HR functions, be it screening applications, scheduling interviews or, onboarding the new employees, every segment will be well taken care of. Not just that but, the administrative jobs that the HR have to do repetitively could be automated too.
Customize your customer journey
Customers like to be pampered, when they shop from big brand names they hardly get to experience that personalized approach. The trendy products aimed at mass-market leave them wishing for something that would suit their style. Retail Analytics Courses can help you develop a better understanding of the whole issue.
Being a small business owner you already have the advantage to take care of this issue and you can be near perfect in your approach if you get support from smart AI algorithms that can browse through customer data and detect patterns to help you understand the personal preferences of customers and thereby allow you to modify your products accordingly to suit their needs.
Coupled with AI power you could also improve your logistics to ensure your supply chain does not experience any glitch.
The development of AI platforms programmed to perform specialized tasks need to be recognized by the small business community, only then they would find the motivation to channelize the power in the right direction. They can also consider upskilling themselves with deep learning for computer vision course, to be able to harness the power of AI.
Retail has been one of those smart sectors that embraced the power of AI technology to offer a personalized shopping experience to the customers. Let’s have a look at how AI has been a great tool in helping the stores rake in money.
Be it smart product recommendations by analyzing shopping patterns, or, offering better inventory management solutions today’s retailers are doing it just right. The sector needs to focus on training their employees, as undergoing customer market analysis courses is of paramount importance.
Offer personalized product recommendations
This has been one of the most revolutionary changes in the e-commerce industry. With AI-powered technology retailers can offer personalized product recommendations to the customers. Using smart tools they can analyze the shopping preferences, shopping patterns of a customer as well as their browsing history.
The data provides them with valuable insight which they apply to recommend products following that specific customer need. By doing so, they can retain customers and experience a better conversion rate. Tools such as Stitch Fix, Boomtrain are carrying out this task successfully to recommend products that suit customer whimsies.
Smarter inventory management
Inventory management is one of the key areas the retailers have to focus on. Previously they would just stock up on items without having access to any valuable customer data. Now that they can sift through big data, they can analyze past trends and could predict what upcoming trends are to look out for. Being armed with data they now make decisions accordingly.
In fact, to ensure that there is no gap in the supply chain robots are being put to use. Self-scanning robots used by Walmart could be a case in point here. These robots look for items that need restocking. Some stores are going one step further to use algorithms to analyze receipts to find out which products are in most demand and they restock accordingly.
Virtual assistants taking care of customers
Customers have no access to virtual assistants, chatbots who not only offers constant support but, also interacts with them offering personalized recommendations, as these bots are powered with NLP technology, they are more intuitive and capable of engaging with customers. In fact, with automation being available, sending a faster response to customer queries has also become more efficient. Navvi is a robot that handles customers along with handling other responsibilities.
Enabling shoppers to take immediate action
Any average person these days spends a good amount of time browsing through social media platforms, different sites which more often than not are used as advertising platforms. So, when a prospective customer finds something interesting, they check it out and then they go on to something else and later might forget about it.
But with AI-powered tools like Lens feature, they can capture the image of the product they like and search for it, thereby ensuring that they can embark on their shopping quest. This feature was initially introduced by Pinterest. With further application of deep learning for computer vision with python, there could be more developments in the field.
Taking chaos out of shopping with smart solutions
When buyers visit a store physically or, virtually they usually browse through scores of products to find what they need. Oftentimes they have difficulty locating the product they had selected online in the physical store. But, with a unique tool like Amazon Go, they can completely be at ease.
They can select the items and put in a virtual basket and when they enter the physical store they can easily track the items they had previously selected and that’s it. No complications involved and they enjoy seamless shopping experience. Zara takes a step further and deploys robots who fetch the product ordered and delivers it.
Identifying prospective leads
AI has introduced some exclusive features such as face recognition, which is being now utilized by retailers to target potential leads. This is leading to a seamless merger of experience one might get in a physical and virtual store. Face recognition feature is being used to find out which products customers are spending time on in the store and based on that, recommendations are being sent online.
The shoppers are no doubt having the time of their lives enjoying this digital shopping experience, they are now able to find and buy products they need instead of wasting money on something random. The retail sector is all set to take the next big leap with AI. Retail Analytics Courses are going to be in demand as the sector needs personnel who are proficient in data handling.
Over the last couple of years we have witnessed an exponential growth in the AI domain. The expansion of AI along with its various subsets are being acknowledged and adopted by different sectors to garner benefits from its various applications.
The manufacturing companies are among those few smart decision makers who were quick to realize the deficiencies present in their current system, and how implementing AI technology could help them address those issues. Retail Analytics Courses are being designed to enable the future professionals to better handle the challenges of the sector.
The key challenges in manufacturing
Before we can proceed to discuss the ways AI is being incorporated in manufacturing, we need to have a thorough understanding of what are the key problem areas this sector faces on a regular basis to realize how AI can tackle those issues.
Operational efficiency, operational safety, inventory control, maintaining product quality, lower operational costs and demand forecasting are some of the issues the companies basically deal with.
Now have a look at how incorporating AI can benefit the companies and in which ways
Ensuring product quality
It is of utmost importance for any manufacturer to ensure that the products are absolutely flawless. So, the products undergo different stages of checking by trained and experienced professionals. But, despite so much precaution being taken faulty products do make their way into the market resulting in customer complaints and the company having to recall the product line. This could be a damaging factor for the brand.
However, with smart sensors in place, even tiniest of errors could easily be detected. Machine vision can scan the products when they are in the production stage and after spotting a problem sends alerts. Professionals having a background in computer vision course python, would be assets for this sector. Nokia’s machine learning based video application can be an excellent case in point as it allows to detect and rectify mistakes in real-time.
Achieving better maintenance standards
Asset failure is one of the key issues that bug manufacturers, due to untimely upkeep and lack of proper maintenance strategies, machines can breakdown often bringing the whole production process to a standstill mode.
Predictive analysis can solve this issue and ensure enhanced operational efficiency. It involves the application of analytics, sensors to keep the machines in check on a regular basis so as to detect any problem areas that need to be repaired or, replaced. This ensures that machine downtime does not impact the production process in any which ways and this also extends life span of machines. Roland Busch, Thales SA, are some of the companies that have successfully implemented and benefited from predictive maintenance technology.
Achieving efficiency in designing process
AI powered technology can definitely boost the designing procedure by taking the whole assumption factor out of the process. Predicting consumer behavior and deciding what products customers are looking for to come up with a design that matches that particular criterion is essential. A degree in customer marketing analysis trainingcould enable a professional be proficient in this job.
Generative design software takes hassle out of the design process, it basically processes data regarding the criteria, different parameters, restrictions, time and budget constraints and offers solutions on the basis of that and also offers insight regarding which design might work best.
Prioritizing security
Ensuring safety of the workers in any manufacturing unit is of utmost importance. Despite taking precautions and safety measures being in place accidents occur due to human error.
To minimize the risk factors AI powered industrial robots can be used in the plants and manufacturing units. The bots will process real-time data and analyze that to minimize risk in a hazardous work situation where human workers could be vulnerable. Since, these bots would be able to analyze data with precision there would be less room for errors.
Manufacturing companies are already applying AI techniques to ensure safe and efficient production environment. The hybrid workforce comprising human and robots , has already become a reality, in future more tasks could be allotted to robots to automate production process and reducing operational costs.
In order to retain jobs in the coming future one has to undergo specialized training such as deep learning for computer vision with python to land a job, because no matter how you look at it the future certainly belongs to AI.
Market researchers usually have a hard time preparing and conducting surveys to gather valuable data on customers as well as competitors and sorting that data to offer actionable Intel to marketing heads to enable them to devise marketing strategies accordingly.
So, basically their job centers around data, data, and more data, it is solely reason enough for them to consider ditching their jaded and often erroneous data collecting system and step into the domain of AI by pursuing customer market analysis courses.
How Market Researchers View AI
Despite recognizing and appreciating the manifold advantages of AI, some uneasiness lingers in most industries regarding its applications and full integration.
However, market researchers were thankfully, quick to recognize the pros the AI package has to offer. The implementation of AI would take most of the hassle way from their job. Surveys conducted over the past couple of years show that almost 80% of market researchers are in favor of AI and they believe that it will be the harbinger of new opportunities.
How AI Can Address the Woes of Market Researchers?
Any conversation with a seasoned market researcher would reveal the issues that continuously bug them. A huge amount of time and money that go into the process along with the enormity of data they have to process, can lead to frustration.
With rampant consumerism becoming a reality of modern society, the market researchers would need to deal with an even bigger amount of data.
Some agencies have already started migrating to AI solutions to address these concerns and they are seeing the difference already. Machine Learning Using Python is becoming a trend which they are veering towards.
Although companies are still holding back from fully integrating AI into their operations, in near future the scenario might change considering the benefits AI can offer
Shortening data processing time: Usually, it takes months to complete projects, but, with AI-powered tools, the duration of the projects can be shortened. Data processing and producing insight based upon data findings can be almost instantaneous.
It would enable the marketing heads to tackle issues faster than ever before, thus gaining an edge over the competition. Report generation would take less time and the team can be employed to handle some other productive tasks.
Higher efficiency in data handling: Any organization has to deal with a huge amount of data, as every year new data gets added to their database. However, when it comes to market research, mostly experience data is put to use while operational data which is mainly old data is shifted to the backburner. AI integration can solve this issue by combining both data sets, and combing through this massive data to produce insights and find new patterns in customer behavior which was earlier missed by your team.
Improve survey quality:
Implementation of AI can take the errors out of the present survey system and make it more efficient. Using ML and NLP, survey questions can be shaped in a conversational style which would immediately put the respondents in a comfort zone thereby improving the chance of eliciting an accurate response. AI-powered tools can also put together a list of respondents who are apt for the survey and eliminating random ones out of the list.
Customize marketing strategy: As AI gets integrated into your market research process, it starts analyzing customer behavior by going through the bounce rate, as well as login data. As a result, it points out those customer, marketing teams need to work on. They get a chance to customize a marketing strategy for them.
There is no denying the fact that AI can transform the way market researchers work. Integration and adoption of AI would certainly take time but, eventually, the merger would happen. Since AI is a highly specialized domain, the market research teams need to upgrade themselves. Enrolling in a premier artificial intelligence certification in delhi ncr, would help them be prepared for a smarter future.
The digitization of modern classrooms is an indicator of the fact that educators have decided to adopt tech to make learning a more rewarding experience for their students. In fact, some educators are making an effort to upgrade themselves with advanced courses like deep learning for computer vision with python.
But, not all children in a classroom can blend in with their classmates with ease, they have difficulty understanding teacher’s instructions or, even following what is written in the textbooks.
Yes, we are talking about children with disabilities, who cannot be taught in a typical classroom setting and who need special attention and today we are going to learn whether the transformative power of AI can make a difference in the lives of these differently-abled children.
How do we classify children who need special education
Children who have been detected with some form of physical, cognitive or learning disabilities such as ASD- Autism spectrum disorder, Dyslexia, hearing, or visual impairment, require a learning environment that is specifically designed for them.
What are the challenges they face in a traditional setting?
Usually, these children have problems coping with the traditional learning environment. They find it difficult to follow instructions, lessons, even their textbooks. They need personal attention from the teacher, and are unable to handle the pressure of competition.
What’s more, these children usually are subjected to bullying from other students, which can further discourage them. they need special tools, and lessons that are designed for them. These children also have a short attention span so, the reading material might not interest them.
How AI can be of help?
The introduction of AI in special education has opened up new avenues for both parents and teachers. Data Science training has enabled professionals to analyze student data to identify problem areas. There have been several studies on this and the findings are promising. With the application of AI-based methods, it is possible to help these children exercise more freedom as it allows them to learn at their own pace.
The Application of AI in special education is aimed to serve a dual purpose.
1) AI-based tools are used to detect disability
2) AI-based learning tools and methods are being adopted to aid learning
Now let’s take a brief look at how this dual application of AI is taking place and with what effect
1) AI-based tools are used to detect disability
Sometimes identifying a problem can lead you to the right solution. Usually, children who show apathy to learning or, are very slow to pick up lessons, treated as dumb. They are bullied and teachers keep complaining that they do not make an effort. But, what they fail to realize is that the child might have a learning disability.
But, now we have AI-enabled testing systems in place to detect children with learning disabilities.
In the year 2008, a model was introduced to diagnose autism with the help of artificial neural networks technique. Even before this way back in 2003, a fuzzy cognitive map approach was taken to diagnose SLI or, speech-language impairment. Other systems involving artificial neural network techniques were developed to detect issues like dysgraphia, dyslexia.
More data based research work on this is required. This would definitely create a demand for professionals who have undergone specialized training on neural network course python.
2) AI-based learning tools and methods are being adopted to aid learning
Children with special needs must have access to special learning tools that would make learning easier. There has been some considerable progress in this field.
Children with Autism have problems with both verbal and nonverbal communication. Developing social skills can be a challenge for them. To address this issue QTrobot was designed. This humanoid social robot is programmed to teach autistic children social skills. Other examples would be NAO robot, virtual assistant Siri which help children with ASD acquire more social skills.
ActiveMath employs Artificial Intelligence techniques to ensure children can have more freedom in selecting a convenient learning environment.
Spontaneous participation of the learner is essential for any learning process to be effective. If a child is having trouble concentrating then, he won’t learn anything. Smart Tutoring model was developed to evaluate the concentration level as well as the mood of the child, to develop a learning session that suits that particular child.
Widex’s Evoke is an intelligent hearing aid powered with AI technology which can help hearing-impaired children attend classes without any difficulty.
AI has the potential to transform the special education sector with advanced learning aids, specifically designed for differently-abled students. The field is expanding and it needs more research and collaboration among educators, app developers, engineers to come up with smarter solutions.
AI is a dynamic field that is constantly evolving thanks to the continuous stream of research work being conducted. The field is being reshaped by emerging trends. In order to keep pace with this fast-moving technology, especially if you are pursuing Data Science training you should learn about the latest trends that are going to dominate this field.
Digital Data Forgetting
It is a curious trend to watch out for as instead of learning data, unlearning would take precedence. In machine learning data is fed to the system based on which it makes predictive analysis. However, thanks to the growing channels and activities the amount of data generated is increasing, and a significant portion of which might not even be required and which only contribute to creating noise.
Although it is possible to store the data utilizing cloud-based systems, the price an organization will have to bear for unnecessary data, does not justify the decision. Furthermore, it might also raise privacy risks in the future. The efficient handling of this data lineage issue requires systems that will forget unnecessary data so that it can proceed with what is important.
NLP
Now that chatbots are being put to use to provide better customer support, the significance of NLP or, natural language processing is only going to increase. NLP is all about analyzing and processing speech patterns. There is now a shift towards developing language models around the concepts of pre-training and fine-tuning and further research work is being conducted to make these systems even more efficient, however, the focus on transfer learning might lessen considering the financial and operational complications involved in the process.
Reinforcement Learning
This is another trend to look out for, reinforcement learning is where a model or system learning involves a preset goal and is met with reward or, punishment depending upon the outcome. This particular trend might push AI to a whole new level. In RL, the learning activity is somewhat random and the system has to rely on the experience it has gained and continues to learn by repeating what it has learned, and as it starts recognizing rewards it continues working towards it until the learning takes a logical turn. Research works are being conducted to make this process more sophisticated.
Automated Machine Learning
If you are aware of Google AutoML, then you already have an inkling of what AutoML is. It basically focuses on the end-to-end process and automates it. It applies a number of techniques including RL, to reach a higher level of accuracy. It works on raw data and processes it to suggest a solution that is most appropriate. It basically is a lifesaver for those who are not familiar with ML. However, there are programs available that enable professionals pursue Machine Learning Using Python who are looking to gain expertise in this field.
Internet of Things
IOT devices are a rage and they are able to collect a huge amount of user data that needs to be processed to gather valuable information. However, there could be certain challenges involved in the data collection process which lead to error. The application of ML in this particular field can not only lend more efficiency to the way IOT operates but it can also process a large amount of data to offer actionable insight. The information filtered this way could help develop efficient models for businesses and various other sectors. The merger of IOT and ML is definitely a trend that is definitely going to be revolutionary.
AI technology is getting more sophisticated with emerging trends. The manifold application of AI is opening up new career avenues. Enrolling in a premier artificial intelligence training institute in Gurgaon, would be a good career move for anybody looking forward to having a career in this domain.
