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How Data Science is Revolutionising e-commerce(Rank Princess-SEO)

In the digital world that we live in, there is more data than ever.  That means more information about everything that surrounds us. Now, this information can be used to do some pretty amazing things, and the present e-commerce Industry is a shining example of that.

About Data Science

Data Science refers to the interdisciplinary study of the scientific methods and processes used to manage the source of data, understand its representation and convert it into useful information.

Every organization generates a lot of data from the consumers through the services that they use. Data scientists can help those organisations use that data to serve those consumers even better.

e-commerce Supercharged

In the business world, it is a self-evident fact that for any business to serve its customers well, it has to know those customers and their preferences and then craft their business plan accordingly.

Traditionally, this was done by the store operators and other executives who directly interacted with the customers. They had a pulse of the market and the direction in which the wind was blowing. But this method was inefficient and barely useful in the long run, and not to mention unusable in the e-commerce industry. This is where Data Science comes in.

  1. Knowing Customers

The biggest aid Data and Data Scientists provide to e-commerce businesses is in knowing the customers. Companies gain this knowledge through the online behaviour of the consumers: their interests, the product they often view, their possible needs, etc.

This helps the companies to know the consumers as well as they see themselves and simplifies the purchasing process.

  1. Selling Better

Data scientists have revealed that consumers’ buying pattern and brand loyalty is ever-changing and not as predictable as previously thought. This has made gaining consumer insight even more crucial for any e-commerce business.

Data sciences have provided the answers to various questions that have enabled the companies to sell better, such as:

  • What demographic of people are buying your products?
  • Which products interest your consumers?
  • How can you contribute to the shopping experience of your consumers?
  • What encourages the consumers to buy the products that they do?
  1. Marketing Done Right

Data Sciences has revolutionized marketing as a whole. With information collected from users about their spending habits, browsing and shopping patterns, more personalized marketing campaigns can be implemented.

These things have helped the businesses with advertisement retargeting, channel mix optimization and have increased the overall attentive time spend by the consumers on the company’s adverts.

This means more specific commercials for the end users and more effective marketing campaigns for the businesses.

On the Flip Side

Whenever the topic of collecting information from the public comes up, questions of security and privacy emerge. This is only natural as cyber security is a pivotal part of the digital lives that we lead.

Companies ensure users’ privacy through ever-updating encrypting technologies and firewalls. And to further enforce security, it is made sure that the sensitive data of users are stored locally on their devices and not on the cloud.

To say that the world of e-commerce has changed forever by Data Sciences would not be an understatement. And with more data scientist working together to further enhance our shopping experience, the future is only looking brighter.

LSI Keywords

Data science in e-commerce

Applications of data science

Online retail and data science

Data science and marketing

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How Data Science is Revolutionising e-commerce(Rank Princess-SEO)

How Data Science is Revolutionising e-commerce(Rank Princess-SEO)

In the digital world that we live in, there is more data than ever.  That means more information about everything that surrounds us. Now, this information can be used to do some pretty amazing things, and the present e-commerce Industry is a shining example of that.

About Data Science

Data Science refers to the interdisciplinary study of the scientific methods and processes used to manage the source of data, understand its representation and convert it into useful information.

Every organization generates a lot of data from the consumers through the services that they use. Data scientists can help those organisations use that data to serve those consumers even better.

e-commerce Supercharged

In the business world, it is a self-evident fact that for any business to serve its customers well, it has to know those customers and their preferences and then craft their business plan accordingly.

Traditionally, this was done by the store operators and other executives who directly interacted with the customers. They had a pulse of the market and the direction in which the wind was blowing. But this method was inefficient and barely useful in the long run, and not to mention unusable in the e-commerce industry. This is where Data Science comes in.

  1. Knowing Customers

The biggest aid Data and Data Scientists provide to e-commerce businesses is in knowing the customers. Companies gain this knowledge through the online behaviour of the consumers: their interests, the product they often view, their possible needs, etc.

This helps the companies to know the consumers as well as they see themselves and simplifies the purchasing process.

  1. Selling Better

Data scientists have revealed that consumers’ buying pattern and brand loyalty is ever-changing and not as predictable as previously thought. This has made gaining consumer insight even more crucial for any e-commerce business.

Data sciences have provided the answers to various questions that have enabled the companies to sell better, such as:

  • What demographic of people are buying your products?
  • Which products interest your consumers?
  • How can you contribute to the shopping experience of your consumers?
  • What encourages the consumers to buy the products that they do?
  1. Marketing Done Right

Data Sciences has revolutionized marketing as a whole. With information collected from users about their spending habits, browsing and shopping patterns, more personalized marketing campaigns can be implemented.

These things have helped the businesses with advertisement retargeting, channel mix optimization and have increased the overall attentive time spend by the consumers on the company’s adverts.

This means more specific commercials for the end users and more effective marketing campaigns for the businesses.

On the Flip Side

Whenever the topic of collecting information from the public comes up, questions of security and privacy emerge. This is only natural as cyber security is a pivotal part of the digital lives that we lead.

Companies ensure users’ privacy through ever-updating encrypting technologies and firewalls. And to further enforce security, it is made sure that the sensitive data of users are stored locally on their devices and not on the cloud.

To say that the world of e-commerce has changed forever by Data Sciences would not be an understatement. And with more data scientist working together to further enhance our shopping experience, the future is only looking brighter.

LSI Keywords

Data science in e-commerce

Applications of data science

Online retail and data science

Data science and marketing

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How Is Data Science Revolutionising e-commerce? (Rank Princess- SEO)

Geoffrey Moore once compared companies without data analytics with deaf and blind deer on a freeway. And Moore was quite right too!

 Any online transaction between a shopper and a seller is a negotiation. And in every consultation, knowledge conjures power. Right kind of information about the other party gives you leverage. And leverage lets you squeeze a better deal where you reap the benefits.

 As a shopper, the sites you visit, the products you browse, the models you put in your cart only to dismiss the window and buy the same item from some other website- that data is significant for a seller. How? Let’s see!

 Business Analytics in e-commerce- Can You Optimise Conversion?

 To guarantee a sale, the seller must:

  • identify the influenceable section of the target shoppers

 

  • figure out what’s important to them, and

 

  • present them with an apt product-deal combination

 

It’s tough! Buyer’s intent is hard to spot. It’s where data science, analytics, & e-commerce    based machine learning come into play.

 Data Science in E-Commerce- How Is the Revolutionising Happening?

 Insights

Sellers use technology to track customer behaviour without disturbing said customer. If a shopper logs into a store Wi-Fi, the software monitors the sections where they linger longer. Marketing teams look at social media and browsing patterns to gather information on trending items.

  1. Prediction

Algorithms study the existing data like product attributes, shopper behaviour, and correlations. They try to infer future trends. They make assumptions based on the data they’re fed about the shopper.

  1. Strategy

Algorithms work to predict what the company should sell when and at what price. The product design, supply-demand forecasting, window of sale, promotional schemes, and personalised shopper targeting are strategized using the learnings of the machine.

  1. Personalisation

As per a 2014 Infosys report, 78{ed162fdde9fdc472551df9f31f04601345edf7e4eff6ea93114402690d8fa616} of consumers respond to targeted ads that focus on their specific interests with a successful purchase.

Sellers use the data and patterns to revisit their retargeting plan, reach to a client of a particular age, interest, gender, and demographic and offer a deal that suits their present concerns.

Why Is Predictive Analysis in e-commerce Needed?

Shoppers often have the advantage of information over sellers. They know the product details and the shopper credentials. They have market reviews and ratings to turn to. They have options from different sellers for one product.

The seller has no way to know what drives the shopper- price, availability, or delivery window. It has to rely on guessing, and that doesn’t work out well in all cases.

Predictive analysis & e-commerce analytics allow the seller to gather fact-based ideas extracted from previous consumer behaviour using machine logic and data science. It helps them optimise conversion, and offer a better customer experience.

Basic Advantages

  • Cross-sell- I see you bought an iPhone 7 recently. Can I interest you in an iPhone case?
  • Up sell- I see you browsing a Full HD LED TV. Here, this 4K is the next version and fits your expected price range too.
  • Personalisation- I have your location. Would you like to see where our nearest store is? Or if we express deliver to your place?
  • Opportunity- I see you are in this country right now that has this upcoming festival that’s apparently a huge thing. Can I interest you in this relevant product that you may need during the said festival?

And That’s Just the Front End

Data science can help e-commerce websites by allowing consumer retention via heightened levels of perception and recognition. But, it can also be used for web analytics, fraud detection, payment, delivery, and other post-purchase aspects that build customer experience.

LSI: business analytics in e-commerce, ecommerce analytics data science, Data Science in ecommerce, predictive analytics in ecommerce

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How Data Science is Revolutionizing e-commerce(Rank Princess- SEO)

Data science as the name suggests is data driven by science. It is a method to extract relevant data or insight from the data in various forms which can either be structured or unstructured. It is kind of similar to data mining.

If we talk about business terms, it helps businesses provide a richer understanding of the clienteles’ by capturing and integrating the information of the prospect’s online behaviour. At this period, e-commerce is the essence of almost every business. The world at this time is immersed in data from many sources. Data science and ‘data scientists’ have revolutionized modern business. With the boom of e-commerce, the aspect of Analysis (“A” from the DMAIC theory) has broadened by leaps and bounds. Before, we talking about the benefits, let’s talk about how it is used in e-commerce.

In the field of e-commerce, customer and sales data are integrated into a database which is further linked with the email marketing and ad platform data. A thorough analysis of these gives a data scientist a 3D view of (i) Customer lifetime value, (ii) Personality analysis, (iii) Churn detection, (iv) Customer segmentation, (v) Cohort analysis, and (vi) Trend analysis. This helps the business to work and forecast new and beneficial acquisition and retention strategies. This is exactly the evolution it has brought to the modern business.

Let me explain it this way – assume you’re on a shopping app/website browsing. You scroll downwards and see that the app/website has recommendations based on your browsing/shopping history. Did you ever ponder as to how the app/website know your preferences and suggests products that you might end up buying? That, my friend, is data science. This method can be classified under Acquisition strategy. You might initially have logged in to the website just to browse, but recommendations have a probable chance of triggering a sale. Another example of it is boosting cross-selling (selling a different product to an existing consumer). Once you select a product, most websites/apps recommend a bundle option of similar or related products. Statistics say that cross-selling is a major part of today’s e-commerce business. As a matter of fact, websites/apps these days also recommend items based on perceived customer journeys. This is also a part of the acquisition. The technique just tells you what other customers have loved so far and thus intrigues a prospect increasing the chances of a successful sale. Retention strategy is when businesses use offers, promo codes, discounts, etc. to a prospect and flash sales to retain market. Big brands use data science and scientists to monitor stock and manage promotions accordingly.

Apart from the above, data science can help a new online business to determine strength and impact of the online vs. physical brand. It can help provide detailed analysis to a retailer on physical shops vs. online sales. Also, the inclusion of data science in online business will help sellers offer personalised deals per customer based on individual browsing habits and patterns. It helps a company to anticipate customer behaviour and understand connections of customer’s product reviews and shopping behaviour with other customers further leading to successful Prediction model (surfing behaviour vs. {ed162fdde9fdc472551df9f31f04601345edf7e4eff6ea93114402690d8fa616} deal-making).

Thus, data science helps to gain sales/conversion providing optimized information about customers. Numbers speak, isn’t it?

Keywords:

Data science

Data mining

Online sales

e-commerce

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Selecting Superheroes: Finding the Perfect Product Manager For Your Startup! (Rank Princess- SEO)

Startups mostly just begin with a simple idea, behind which there may be a singular brain or a whole team. The CEOs along with some designers and sales lead can easily constitute a startup, but the real person holding everything together is the product manager.

In case of a startup, the need of an able product manager is even greater because it is his or her motivation and involvement that will channelize the energy of the whole team; and by large the entire company. A novice in the game can get the idea shattered like a house of cards. While a great product manager will not only continue with the dream of the original creator but take it to even new levels.

Let’s have a look at some of the desirable qualities to look out for before you hire a product manager.

The Hero Your Startup Needs (As Well As Deserves)

While finding the right person, keep in mind that this is the person who shall be handling your dream project. The original idea of the company owner is very dear to them, and the product manager must nurture it as his or her own. There is no scope of backtracking in today’s world. The only way is forward. Always hire a product manager who fully understands the idea behind the company and strives to make it a success.

Be Just the Ticket

The person to be hired must gratify all the requirements excepted of their post. A product manager is like a bridge between all the team members. Therefore, he or she is expected to be multidimensional and have innate leadership skills. In addition to being talented at their work of managing the staff and product, they must also be able to think quickly and make decisions.

The CEOs and other higher officials may not be available all the time as they have to look after other things like promotions, fund-raising, meeting with other company heads, etc.  The product manager must be able to fit into the leadership role, seamlessly. All these must be assessed carefully before selecting a product manager.

Versatility is the Key

Working in the market can be a grueling at times, especially in case of a startup. The needs of the company, as well as the market, can change very abruptly. A person must only be selected if they are adjustable enough to absorb all the irregularities and still provide a good working environment for the team.

They must be able to adapt the company according to client feedback. A good manager must never shy away from incorporating any assessment or criticism to make the product better. While hiring, always keep in mind that a product manager is ultimately the one who can make a product better or worse. That is why it is imperative to hire a product manager with ample room for adaptability.

Smooth Player

Execution makes or breaks a startup. One can put hours of sweat and tears into an idea, yet everything can fall flat if the execution is not proper. The company should look forward to hiring a product manager who can choose the right path forward. And for this, during the selection process, the candidate’s level-headedness under pressure must be evaluated. There are generally many distractions on the way to success; however, a good product manager knows how to make the right choices. After all, it is them who have to manage the competitors, product feedback, customer relations and product marketing.

A product manager must be a multifaceted individual who can look after a lot of things in the startup. He or she has to be able to act as a leader and at times, a subordinate. Most importantly, a product manager must take care of the customer feedback and comments from the market, at the same time keeping up to date with the competitors. While all this seems quite a lot for one individual, but today there is no dearth of talent out there; and with a hint of luck, you can get the perfect product manager for your dream venture.

Primary Keyword:hire a product manager

LSI Keywords:Finding the Right Product Manager,candidate’s level-headedness under pressure, multifaceted individual

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The Best PM For Your Startup?(Rank Princess- SEO)

Should your startup have a person exclusively for taking care of your company’s products? If you ask me, the answer is yes since startups have to operate in a dynamic environment.

The offer of the startups needs to be constantly tuned to the market opportunities and demands. You should hire a product manager who can think about your products and how to make them a zipping success. The person will be responsible for innovating product ideas based on product and market research.

Who Can Be A Product Manager?

Qualifications

A product manager should be a person who knows the product and the industry in and out and has management qualifications with specialization in marketing. If your startup has a technical product, then the product manager needs to have technical as well as marketing specialization.

Reporting

Before having a product manager the product management function was most probably being looked after by you the founder(s) of the startup with the assistance of team members. The appointed product manager should be given due authority to seek required inputs and information from the startup team members and should report to the founder-entrepreneur(s) of the startup.

Experience

Product Manager is a senior position than product executive hence some experience in product management of similar products is also desirable. Experience of three to five years would be most suitable for your reporting structure. If you are impressed with ]fresh talent, then you can assign product executive role during probation and confirmation as a product manager.

Skills and Aptitude

Your product manager besides having the desirable qualifications and experience needs to have a penchant for the challenge and a love for innovation. The person should be driven by growth and achievement motives.

What Can Be The Selection Procedure?

Source Of Applicants

Recruiters can opt for internal as well as external selection to hire a product manager. The vacancy announcement should spell out the candidate profile which should be in sync with the job description and key responsibilities.

Written Or Online Test

Eligible candidates can be assigned a written or online evaluation to test for product and industry knowledge as well as marketing and innovation aptitude. You can yourself set up the test or provide your inputs to the test setter.

Personal Interview

Candidates who qualify the written test can be called for a personal interview with you. During the personal interview, you can ask the candidate the reason for preferred job profile, industry and company and the candidate’s expectations.

Selection Method

Quantitative scaling method is an objective and simple selection method. The candidate’s qualification, experience, personality, performance in written test and interview can be scored on a scale of five. Parameters can have sub-parameters. The individual scores of the sub-parameters and parameters should be added up to get the total score and candidates can be ranked with the help of these scores.

Job Offer

The job offer is usually given to the highest scoring candidate. The second highest scoring candidate is called if the first candidate refuses the offer or fails to join.

LSI Keywords: Hire a Product Manager, PM, Product Manager, Product and market research, Product management function, Product executive.

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Hiring the Perfect All-In-One Product Manager(Rank Princess-SEO)

A product manager (PM), is at the bottom-most link of the chain, the job description is such that of an artist, workman and scientist in one. The PM coordinates with many other departments in a company to execute their ideas.

Leadership without authority is what they are duly described as. PM’s are an integral part of the team, in creating a new product, to execute and maintain the product.

A PM is a Role-Player

In big and established businesses PM’s are selected from their qualifications and years of experience as key points. In start-ups, however, a PM is not a specialized field. It is expected that the candidates are multi-tasking and have knowledge of the generalities of other fields.

Hiring of a PM

The eligibility of candidates for being good Pms can be found by testing certain skills and traits:

  • Problem-solving technique: Product manager is a tricky role to play; it requires a lot of creative thinking. They are expected to turn the setbacks faced to a different solution.
  • Communication Skills of candidates should be off the charts. PM’s are a part of the well-oiled machine; they are expected to maintain the status quo in the machine.
  • An attribute that is often expected of candidates applying for PM is empathy: Thinking from the minds of their clients and customers. To create or discover a product that fulfills their wants and needs satisfactorily.
  • Natural leadership ability: they are expected to lead and coordinate with other teams to ensure the product is launched into the market fit.
  • Curiosity for and a thirst to find out new ideas and techniques to make sure the product satisfies the needs of your customers and still is innovative.
  • The failure of any product generally lowers the morale of a team. The candidate is tested on how he can adapt to the failure and glean from the mistakes or challenges is crucial. A PM is also expected to motivate and push for a better product in the future.
  • Passion sums up the attributes that are often seen in a PM. Passion is a tricky thing trait; it needs the drive of motivation and inspiration to ensure that a product is launched successfully in the market.

PM’s Are Expected To Prove Their Worth

A Product Manager is a unit that is expendable at any time. It is required of the candidate to be functional in any other part of the team too. A candidate with strong technical background, leadership and communication skills is not expendable in the least.

The PM is required to be confident in various aspects of the functioning, design, and marketing of the product. Instincts and the innate quality to turn setbacks in favor of product are valued highly in the character traits of the PM.

Product Managers are expected to experience and learn from their failures and push for innovation. In start-up businesses job descriptions of PM require them to do a little bit of everything and work as a part of the team. The perfect Product Manager thrives on the possibility to achieve success.

LSI Keywords: product manager, strong technical background, leadership and communication skills

 

 

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Notes of a Digital Consumer(Content Strategi- SEO)

It is quite hard to imagine a world without technology. We’re well past the point of doing anything without it. To be honest, I don’t really feel like standing in long queues to pay my bills, or even buy something (no exception for a pizza either). These are the days when even my cat has to take lessons in computers to get a grip on his mouse (!). Pun, of course, is intended.

Technology has always evolved at a good pace. The past few years have seen it rise exponentially. We’ve seen the rise of the Internet of Things, cars that can drive on their own and even ‘smart’ cities – capable of performing numerous tasks on their own. How can mere mortals like us cope up with this growth?

Well, here are a few notes I made during my travels in the digital realms.

It’s only a Phone if it’s smart.

The world and everything in it have changed a lot over the last decade. It is hard to remember a time when the internet could only be accessed via PCs or laptops. I could go on to say that it was a simpler time – easier to understand and describe. However, then came the smartphones.

Apple’s iPhone, Samsung’s Galaxy series, OnePlus 5 and even Motorola are household names these days. If I was to go into figures, 44{ed162fdde9fdc472551df9f31f04601345edf7e4eff6ea93114402690d8fa616} of the world’s population owns a smartphone.

We’ve become so used to them that we can’t really go without them. In ways, they’ve made life much faster. You can now connect and control different aspects of your life from your phones. Have a bill to pay? Do it on your phone! Need GPS navigation? Your phone’s got you back.

There have been concerns over the security of our phones, as well as the classic case of “all eggs in one basket.”Nonetheless, Smartphones are an essential part of our lives now – and they’re here to stay.

The IoT Revolution

One of the few ‘fad’ terms that really caught my eye a few years ago was the ‘Internet of Things.’ I had my doubts tough, for I’d heard about too many ‘game-changing’ new technologies to hold my breath. The more I read about IoT, the more useful I found it.

How good would it be for your home to know when you’ll be back and have your water heated up? Seems too futuristic? Well, it’s already here. We can now control almost any gadget that can communicate.

Essentially, anything that can be connected – will be connected. Almost 8.3 billion things will be a part of this ‘revolution’ by 2020. IoT enables you not only the ability to control appliances but also monitor your health. The wearables can track all your movements and then provide you with analyzed results.  Even the toasters are now able to make breakfast for you, without the physically touching part.

Feeling like a Jedi, yet?

IoT has affected us as consumers in a great many ways and will continue to do so. Amazon’s Alexa is probably the best example of IoT and how it is changing our homes.

Even our cities are smart

These are the days where smart meters and grids are used quite a lot. The US is one great example of this. Almost 50{ed162fdde9fdc472551df9f31f04601345edf7e4eff6ea93114402690d8fa616} of their 150 million endpoints are covered under this ‘smart-grid.’

The grid essentially prevents voltage theft and saves energy – helping us save our own money. Long have we paid extra cash to the electricity company. However, that is now changing with the introduction of smart meters – that enable a pay-by-usage model.

As a consumer, this is value for money. Even healthcare is improving, with sensors alerting nearby hospitals about any accident. Effective traffic monitoring using satellites not only enables us to save time but money as well. Google Maps are one such technology that smart cities incorporate a lot to find out about street clogging, traffic jams, and even accidents. Traffic Detection using the RUT9 routers enables a better road efficiency across the entire city.

Better services to us

Big data analytics have picked up their slack over the past couple years. As consumers, we generate a lot of data on a daily basis. Collection of this data and its successful analysis enables companies and firms to provide us with a better service.

Knowledge is power, they say. We can know about a company and the products it offers – all from the comfort of our homes.

Is it worth it?

Definitely, yes. Grown and change are the only constants in this world and technology is a superb instrument for the same. As a consumer, I want comfort, as well as the best goods and services that I can afford. A better tech-savvy world will amount for us to have more time pursuing what our heart desires. One can only hope though, that this doesn’t’ lead to a Terminator-type scenario. 

Source

-None, original article and ideas.

Keywords: Internet of Things, IoT, Smart meters, digital consumer, value for money, wearables, M2M

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Machine Learning – The Effects of Artificial Intelligence(Content Strategi-SEO)

Machine Learning – The Effects of Artificial Intelligence(Content Strategi-SEO)

Machine Learning is an area of technology that has helped to improve the quality of service on the web and our smartphones. The term, often used as a synonym for Artificial Intelligence is pretty distinct from AI, yet, connected to it as well.

I could go on to say that the end goal of AI is to create a machine, capable of mimicking the human mind. To achieve this, it needs learning capabilities. That being said, Artificial Intelligence, as an area of computing is pretty broad. It includes reasoning, representation of knowledge and even abstract thinking. On the other hand, Machine learning focuses simply on software that can ‘learn’ from past experiences.

Machines learning from past experiences? Yes, it’s quite possible! Also known as ‘Analytics 3.0’, it’s closely related to statistical analytics and data mining.

Intrigued? Well, read on.

What is Machine Learning?

Earlier in this article, I’d said that machine learning is quite distinct, yet connected  to AI. Let’s expand that statement. Machine Learning is simply the ‘leading-edge’ of Artificial Intelligence. It’s the field of computing that enables computers (aka, machines) to learn from past experiences, be it success or a failure and use that information to predict outcomes for the future.

To understand this further, let us assume that you have to buy a new house.

There is a small house that’s available for $70,000 and a bigger one that costs $160,000. However, you’d like to buy one that’s medium in size.

Using past trends, and something that’s called ‘Linear-Regression’, your computer can successfully predict the cost of the medium sized house you want. The best part of this is that once you buy it, the sample space increases and the computer will be able to predict an even better price in the future.

Simply put-in, machine learning enables a computer to improve its performance, as it learns from what has happened in the past. Another example can be seen in the simple game, Tic-Tac-Toe. Your software evolves and gets more accustomed to your moves, making it harder for you to win. It learns on the go and makes you think more and more.

How does it all work?

Engineers use quite a lot of different techniques to build systems that are capable of learning. As already mentioned, a lot of these ‘techniques’ are related to the mining of data and statistical analysis. Let us consider the following image:

The top-left image is a data-set. This consists of everything that has happened and is of two types –red and blue. As this example is purely hypothetical, these red and blue dots can represent anything, be it petals on a flower or coins and their diameter.

In terms of pattern, or grouping, you can see that the top part of each image is red, whereas the bottom is blue. Towards the middle, there seems to be some sort of a union. Machine Learning uses different algorithms to predict where a new, unseen sample will be placed. All other pictures in that figure are different algorithms, which you needn’t know (Unless you’re an engineer!).

Machine Learning: Use cases

  1. Climate Change Modelling

With the growth in the number of Earth-observing satellites and climate models becoming more powerful, scientists are turning to Artificial Intelligence and Machine Learning to overcome any deluge of data.

 To put this ‘data’ into perspective, the UK MET office holds about 45 petabytes of information as of now (Although, I wonder what they use it for, as it’ll probably be raining there!). Machine Learning has led to the growth of climate informatics. This has helped officials develop better climate models and predict accurate changes in weather.

This has further evolved into correct predictions for tropical cyclones, atmospheric rivers, and even weather fronts.

  1. Autonomous Vehicles

Since computers have the ability to continuously learn from experience, discern their surroundings and come to accurate results, more developers are working towards autonomous vehicles.

The number of ADAS (Advanced Driver Assistance Systems) have increased in numbers over the past years. They’re expected to reach a total of 122 million (!) by 2025. These autonomous vehicles use multiple cameras, sensors and radar systems to analyze and adapt to a rapidly changing environment.And with deep learning, they can know the behavior of other vehicles on the road, making for a save mode of transport.

  1. Medical Research

If the availability of a lot of data is key for machine learning, medicine is a gold-mine. Providing the industry with improved efficiency, optimized innovation, and tool creation, over a $100 billion can be generated – annually.

In 2016, IBM and Quest Diagnostics teamed up and announced the IBM Watson Genomics, which aims to integrate genomic tumour sequencing and cognitive computing. Another prime example of  the use of machine learning in medical research is Google’s DeepMind Health.

What machine learning is doing for medical research is simply reaching accurate diagnostics by going through a tonne of data, which can never be studied manually by a physician. Machine learning not only provides speed of diagnostic, but a personalised result report as well.

Machine learning has a lot, lot more use-cases. You can read about Forbes’s top 10 following this link.

Worth all the hassle; and the risk?

Have you ever watched the movie Terminator? Before going further, I have to say that it peaked with Judgment Day. Plus, they shot the heart out of dear ol’ Arnold in that new one…

Anyway, I really do not wish to live in a world that is ruled by machines. As with all things that aim to change the world, there’s a moral component with machine learning and AI. What will happen if Artificial intelligence outstrips our own and someday becomes bigger than humanity? Facebook did shut down it’s AI program after robots started to develop their own language. There will also be times when the decision a machine makes, while as good as it may be, it might not be morally right for us to follow.

The BBC did a wonderful piece on the above, which you may read here.

As for risk assessment, some machine learning strategies can fail up to 90{ed162fdde9fdc472551df9f31f04601345edf7e4eff6ea93114402690d8fa616} of times when applied to a real-life situation. So, is it worth the try, and the risk? At this point of time, I’ll go with a tentative yes. I suppose it’s just a case of ‘we’ll deal with the future when we get there!’

Final note

Machine Learning, unlike many areas of Artificial Intelligence, is not intangible. It is already here and is continuing to improve our services and daily lives. That being said, it is not perfect, nor will it be for the foreseeable future. This is simply because of the fact that not all data we feed the machines are perfect.

Perfection though, is a journey, and as we grow as humans, so will our machines and gadgets. The trust between them and us will grow steadily, and transparency in algorithms may help it develop faster.

And in my humble opinion, this ‘learn-by-doing’ process is pretty good, so we might as well work towards making it even better!

Sources:

http://www.bbc.com/future/story/20161110-the-real-risks-of-artificial-intelligence

https://www.techemergence.com/machine-learning-in-pharma-medicine/

https://www.informationweek.com/big-data/big-data-analytics/ai-machine-learning-drive-autonomous-vehicle-development/d/d-id/1325906?

https://www.nature.com/news/how-machine-learning-could-help-to-improve-climate-forecasts-1.22503

https://www.androidauthority.com/what-is-machine-learning-621659/

https://www.forbes.com/sites/bernardmarr/2017/07/07/machine-learning-artificial-intelligence-and-the-future-of-accounting/2/#3651a26ef510

https://www.coursera.org/learn/machine-learning/lecture/Ujm7v/what-is-machine-learning

http://www.expertsystem.com/machine-learning-definition/

https://www.youtube.com/watch?v=63NTeLmDANo&t=5s

https://www.youtube.com/watch?v=f_uwKZIAeM0

https://www.youtube.com/watch?v=IpGxLWOIZy4&t=551s

Hyperlinks:

  1. http://arxiv.org/abs/1605.01156
  2. http://press.ihs.com/press-release/artificial-intelligence-systems-autonomous-driving-rise-ihs-says
  3. http://www.mckinsey.com/industries/pharmaceuticals-and-medical-products/our-insights/how-big-data-can-revolutionize-pharmaceutical-r-and-d
  4. https://www.mskcc.org/ibm-watson-and-quest-diagnostics-launch-genomic-sequencing-service-using-data-msk
  5. https://deepmind.com/applied/deepmind-health/research/
  6. https://www.forbes.com/sites/bernardmarr/2016/09/30/what-are-the-top-10-use-cases-for-machine-learning-and-ai/
  7. https://www.forbes.com/sites/tonybradley/2017/07/31/facebook-ai-creates-its-own-language-in-creepy-preview-of-our-potential-future/#280a7cdc292c
  8. http://www.bbc.com/future/story/20161110-the-real-risks-of-artificial-intelligence
  9. https://www.bloomberg.com/news/articles/2016-11-10/why-machine-learning-models-often-fail-to-learn-quicktake-q-a

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Working Out at Home Isn’t Just Possible, It Might Even Be Better (Rank Princess-SEO)

To be healthy: A goal so simple, and yet it’s saddening how often people begin their fitness journey but give up on it mid-way. Been there? Of course, you have! We all have. But don’t blame yourself anymore. This time it’s going to be different.

Yes, we know that you’re busy. Yes, we understand the household pressure as well. But what we don’t understand, however, is you letting those factors become a roadblock on your journey to a healthy, better body. It doesn’t have to be that way. Read on to find out why it won’t.

Why Plans Crash

You not being able to join a fitness regime could be attributed to various factors:

  • Lack of a good gym nearby.
  • Unavailability of dedicated time for working out.
  • Unaffordable gym memberships and associated costs.
  • Lack of proper guidance at the gym.

There could be other reasons as well stopping you from achieving the body you desire. Truth be told, the fault lies in the very operating model of the fitness industry. While all gyms do a great job at making us sign up for their annual packages, very little is done to keep us going.

It is for these reasons that the effectiveness of gyms and other fitness programs is sometimes questioned. The solution? Remove fitness centres from the equation and keep the regime. Sounds impossible? Welcome to Mobiefit.

Fit at Home

The founders of Mobiefit realised the need for personalised and professional fitness training that can be availed without leaving the house. The result was the Mobiefit Body app.

The Mobiefit app allows you to work out your entire body at home without using any equipment at all. You read that right: zero equipment.

For the development of the Mobiefit Body app, the development team worked closely with fitness experts and personal trainers to ensure that you get the very best of what the health and fitness world has to offer.

How it Works

The effectiveness of the app lies in its simplicity and adaptability. The Mobiefit Body app doesn’t have a fitness plan for all of you. It has a fitness plan for EACH one of you. The app works closely with you to understand your needs, goals, available time, and work out area and complies a fitness regime that is unique to you.

When you’re working out at home, your work out revolves around body weight exercises. These are the exercises that use, you guessed it, the weight of your body to activate your muscles and tone your physique.  The app has a library of over 250 training videos and over 47 exercises. You simply feed your initial physical data, goals, workout intensity, and you’re good to go. You will receive personalised guidance to perform those exercises and advance through your program.

The app calculates the duration of your workout, the calories burnt, the number of sets of each exercise performed and keeps track of this data to compile a chart of your progress over time. The included challenges will keep you focused and hungry to reach your goal. The more you achieve, the more you’ll be motivated. The more motivated you are, the more you’ll achieve.

Is It for Me?

Do you wish to be healthier tomorrow than you are today? If yes, then the app is for you. So, whether you are a busy professional who can’t allocate gym time, a student bearing the burden of exam prep, a homemaker who’s too caught up in other commitments or any individual who can’t make it to a fitness centre, Mobiefit is for you.

With Mobiefit Body, you save on gym memberships, personal trainers and fancy gym outfits (c’mon let’s be honest) and avail great personalized training at any time you want, at the place of your choice.

All you have to do is make a choice: A choice to leave behind the life of procrastination and negligence of your health; a choice to take control of your health and doing something for it. All you have to do is make these simple choices, and we promise you that your body will thank you for it.

LSI Keywords

Working out at home

Home workout plans

Mobiefit health plan

Mobiefit Body app

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12 Easy Home Workouts Lose Muffin Top

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