Mohan | Digital Marketing Consultant

The notion of using data to predict future outcomes is far from new. Even highly technical products that performed “predictive analytics” analysis have already been available to enterprise organizations for many years. The notion of developing and deploying custom-built predictive solutions, however, have, for the most part, been the exclusive domain of Fortune 500 companies. The rarity of predictive analytics in the enterprise is mostly due to the technical complexity needed to create, train, and deploy the complex AI and Machine Learning (ML) models required to successfully develop predictive solutions. Over the past few years, the world of AI and ML development has seen rapid change. One of the most critical areas of progress has been the automation of the training of ML models. The advent of “AutoML” platforms has allowed data science teams to accelerate the testing and training of ML algorithms and accelerate the development of predictive algorithms. However, the problem...

Increasingly, businesses are looking more and more to the Internet for not only marketing purposes, but for establishing and maintaining relevancy in this digital age. Digital marketing is great for brands for countless reasons; however, what many companies forget when attempting to re-connect with its audience online is that a brand’s own website is viewed as a representation of the organization’s overall image. If that website is not designed in a manner that is user-friendly, the brand’s image may be negatively impacted as a result. This is why it is important for web designers to know the fine art of developing visually-stimulating, engaging sites that are user-friendly for both human visitors and search engine spiders alike. If the search engines are not finding your website online (unless you have a popular brand name), chances are your audience cannot find you either. Although there is no real set of “standards” for website design, here are six simple, easy to incorporate rules ...

  It is true that no one can ever get tired of shopping. Cyber Monday and Black Friday of 2013 came and went away, but shopping is one such thing that never loses its craze and charm. In fact, we do not even wait for certain dates to get special discount offers; rather, we keep on buying stuff all around the year. While some consider it as a stress-buster, others look at it as an effective way of staying happy. Recent reports show that our fascination with shopping increased ten-fold after the rise of e-commerce websites. As competition is so stiff, an e-commerce retailer cannot afford to lose a single customer, especially during the holiday seasons. This is the reason an e-commerce retailer must make sure that his website is of the very best quality. A small e-commerce business, in particular, needs to grasp this opportunity during the peak selling seasons. As the recipe to success is present in the e-commerce website, there are certain adjustments that a small e-commerce business...

Despite the huge contributions of deep learning to the field of artificial intelligence, there’s something very wrong with it: It requires huge amounts of data. This is one thing that both the pioneers and critics of deep learning agree on. In fact, deep learning didn’t emerge as the leading AI technique until a few years ago because of the limited availability of useful data and the shortage of computing power to process that data. Reducing the data-dependency of deep learning is currently among the top priorities of AI researchers. In his keynote speech at the AAAI conference, computer scientist Yann LeCun discussed the limits of current deep learning techniques and presented the blueprint for “ self-supervised learning ,” his roadmap to solve deep learning’s data problem. LeCun is one of the godfathers of deep learning and the inventor of convolutional neural networks (CNN), one of the key elements that have spurred a revolution in artificial intelligence in the past decade. Self-su...

  Mobile applications (or mobile apps, in short) are software applications that run on mobile devices. Normally, mobile apps get divided into 3 categories – mobile web apps, mobile native apps and mobile hybrid apps. There is another interesting way to group these apps. Based on the kind of functions a mobile app performs, here are the most popular types of mobile apps: #1. Personal Assistants These apps get designed to handle daily tasks. Some popular examples of these apps are reminders, notes, calendar, stopwatch and alarm clock. However, extra utilities can help enhance their powers and make them work better. These utilities make it possible for them to convert, estimate and calculate in a better way. For example, utilities can help turn a screen into flashlight, and scan QR codes. In short, these apps help increase a mobile user’s productivity. #2. Geo-location Guides Geo-location guides or GPS-powered guides are one of the most popular apps. The GPS guide allows users to use ...