Machine Learning

From Logo Design to Machine Learning: A rapid change in Information Systems

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Technology has always been perceived as something that brings about a transformation – a change. There were simpler times – and there are times when things got complex. But the ultimate aim of technology has always been – to simplify the complexities – whether in business, in daily life, or in any aspect of work. Things as simple as logo designs were done manually – and then were drafted using creative technology. There was a time when people believed that what was a drawing without a paintbrush and canvas – today – digitally – creations exceed beauty and delight.

From Logo Design to Machine Learning - A rapid change in information systems

Machines that learn from patterns

Well, information and its analysis also saw a similar transformation. All IT systems have the ability to gather logs of what’s happening and what’s not. That’s a lot of information at hand which can be used, but – not without making ‘sense’ of it. When this available data is analyzed and made use of to predict and fix things or offer services, this data becomes intelligent information. Businesses use this data to improve business offerings. What good is any system, if we cannot learn from the past to better the future? Well, machine learning has been a boon to the industry which has transformed the way in which things work in many sectors.

Machine learning works on pattern recognition and computers can learn from these patterns to perform specific tasks without having programmed to do so.

Transformation is here!

From simple logo designs to intelligent computers learning from data and patterns, technology has seen a lot of changes and has transformed the way in which businesses work. There will soon be a time when there may not be so much dependency on programming either – how about a self-programming computer – that learns and reprograms itself – and helps other computers too?

Artificial Intelligence

Impact of ML in the Ecommerce industry

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A lot has changed in the ecommerce industry over the past decade. Technology has been one of the most crucial drivers for these changes. With AI and machine learning becoming ever more integrated into our daily lives, ecommerce is not far from being influenced by machine learning. As ecommerce continues to grow by 20% every year, technology will keep playing an important role in how customers interact with online stores. Further, mobiles will be responsible for around 70% of the total ecommerce traffic. Artificial Intelligence and machine learning will enable handling of over 80% of the customer interactions.

Impact of ML in the Ecommerce industry

Here’s how machine learning will impact ecommerce in the near and distant future:

Customer shopping experiences:

Machine learning allows ecommerce businesses to create more personalised customer experiences. Customers prefer to communicate with their favourite brands and ‘expect’ personalization in the communication. Machine learning can learn your shopping habits and preferences and hence offer more relevant suggestions and other communications.

Search results:

Improving search-results means more business for ecommerce stores. Machine learning can improve ecommerce search results by taking into account personal preferences and purchase history. Machine learning can create search ranking based on the relevance of the page for that particular user – unlike the traditional search methods that uses keywords.


Artificial intelligence can use not only customer’s digital data, but also analyse their in-store behaviour. Face recognition software will be used to re-target the ads for that latest product you checked out in-store.

Product recommendations:

Machine learning can be used in ecommerce to recommend products according to patterns in customer’s shopping behaviour. This helps increase conversions.

Marketing guide:

Machine learning can recognize patterns and predict trends so that businesses can find out what people respond to, what can be changed and what can be entirely eliminated from the marketing campaigns. This helps maximise returns on a marketing campaign.

Price Optimization:

Machine learning algorithms can help collect information regarding pricing trends, competitor’s prices and demand for various items – and combine this information with customer behaviour to determine the best price for each of your products.

There are a lot of exciting opportunities for machine learning in ecommerce and it’s becoming a means of improvement in online retail. It makes selling online more effective and rewarding.

Artificial Intelligence

AI for Marketing & Sales: Your Friendly Chat Bot

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One of the most recent buzzworthy technologies has been machine learning. AI and machine learning have completely changed the way people interact with businesses in the most simplistic ways – chatbots. Chatbots are a boon to businesses as they supplement human customer service requirements and help boost sales. These are typically the chat boxes that are seen on the bottom right corner of the screens to interact with website visitors and address some of the basic queries.

Chatbots are rules-based programs that respond to certain words and phrases with preprogrammed answers. Especially for customer service, they are capable of gathering some basic information.

Advanced chatbots use machine learning to create a more authentic and personalized user experience for users. These programs are advanced and can make more informed and less robotic decisions. They have the ability to consider language, context and past interactions before they provide an answer.

For marketing Chatbots can:

  • Create new responses to inputs that weren’t originally programmed, using past data to draw new conclusions.

  • They can be programmed to give customers a friendly greeting like ‘hello’. If the user types a word or phrase that wasn’t originally programmed, it can analyze the phrase and determine another appropriate greeting.

  • Chatbots can improve customer relations by delivering high-quality services that users can access without having to wait.

  • Chatbots are used to increase lead generation and for performing marketing activities, conversational surveys, schedule reservations and even provide users with quotes and pricing details.

  • Some chatbots even help customers find the right products – instead of browsing products on a website. Users can tell the chatbot what they are looking for and the chatbots can return the results to users with the relevant products.

  • Some customer service chatbots can handle hundreds of service requests that companies get. These bots can tackle almost any service call from start to finish by providing information, tracking deliveries and performing automated changes to orders.

Chatbots are becoming one of the niche channels to convert, activate and engage clients. They are becoming more and more natural ways to feed clients with information or even include a call to action in order to close the deal. They could be your next friendly marketing execs!

Data Science

How Data Science and R boost the business analytical model

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Building a model for statistical analysis was a daunting task – playing around with C and C++ and painstakingly building a lengthy program. Even if one thing goes wrong, you would have to pull the whole thing down or start all over – a truly crushing realization.

Thankfully, in the world of technology, things move quickly and in the world of statistical analysis, things have moved faster. It’s now possible to create a system for analyzing data that’s constantly adapting, evolving and improving. One of the best ways to do that is with R.


So, what exactly is R?

R is a programming language with rich features and can be used for all kinds of data science, statistics and visualization projects. R’s popularity is also due to its open source nature with an extensive support network and free tutorials. R is known to be so versatile and powerful that everyone from Google to Facebook is using it to either analyze the news feeds or to assess the effectiveness of its ads. R has enough provisions to implement machine learning too.

Benefits of using R

Here are some of the benefits of using R:

  1. The coding is quite easy and can be implemented easily too.
  2. It’s open source and no need to pay any subscription charges – no recurring costs of any kind.
  3. Availability of instant access to over 7800 packages that are customized to perform various computation tasks.
  4. R has an overwhelming community support and there are a number of forums that will help you in case of any issues.
  5. High performance computing experience.

Beginning in the 90’s, a number of endless efforts have been made to improve the interface and the journey of this language from being a text editor to an interactive studio that can enable data science and statistical analysis is quite a journey in itself!