In an increasingly global market, online retailers need to implement the latest IT solutions to reach their target market and increase sales. And integrating digital technologies into all areas of your e-commerce business will help you stay ahead of your competitors. Here, we’ll take a look at five components of this digital transformation:

Cloud Computing

Cloud computing enables remote employees to work more efficiently and to really feel part of the team. It also lets them have quick access to data and files they need, at any time. There are many online resources available for teams to collaborate effectively. You can try a free PDF editor that lets workers annotate and share files instantly, eliminating the need to send emails while hoping they don’t end up in your correspondent’s spam folder. Instead, online collaborative tools let all your stakeholders create, edit and share documents on one platform, and all your data is kept in one place.

Data Mining

Data mining allows you to extract useful information from your business’s databases and discover patterns and trends. This is especially beneficial for e-commerce businesses looking to improve their customers’ experience. Your online visitors will get the most relevant search results, which will lead to an increase in sales. Buyers will also get recommendations tailored to their needs and wants, based on their previous searches and purchases, and give them options for add-ons or upgrades that can lead them to put more items into their online shopping baskets.

Mobile Apps

Designing mobile apps for your e-commerce business will let shoppers make purchases straight from their smartphones or tablets. Mobile sales have been steadily increasing over the last few years, so make sure your company jumps on that trend and does not miss an opportunity to meet existing and potential customers where they are. Mobile apps will let shoppers discover and buy your products anytime and anywhere; they will help you in your data mining efforts by tracking your users’ location and spending habits.

AI and Machine Learning

With machine learning, companies who follow their customers’ online browsing and spending habits are able to deliver personalized recommendations for future purchases, thus improving the customer’s experience and increasing your company’s potential for sales. Visual search engines help users find products quicker by letting them use pictures instead of keywords, and by displaying related items, e-commerce’s can engage consumers even deeper as they show them new products to discover. Think about optimizing for voice search as well to drive even more traffic to your website and products.


Data protection is one of the main concerns of cybershoppers. Phishing scams, fraudulent websites and fake social media profiles have been proliferating online, and cyber threats are becoming increasingly more sophisticated and harder to spot. By ensuring your e-commerce website and mobile apps are safe, you can build trust with your customers and turn them into loyal shoppers. So remind your team members and customers to stay vigilant, and implement security measures such as two-step verification and passcodes. Conduct a vulnerability assessment of your company, and have a backup plan in place in case of an attack by cybercriminals.

Online shopping has increased exponentially over the last few years, and your e-commerce business can really benefit from a number of online tools and digital platforms. Keep security top-of-mind during implementation, and strive to spot consumer trends so you can meet new demand before your competitors. Meet your customers where they are, and provide them with the best online shopping experience so that they keep coming back to your site and become avid followers of your brand.

At aicorespot.io, we predict, discuss and invent the future. So come be part of our AI-driven community and join the revolution!

A problem with training neural networks is in the selection of the number of training epochs to use. A lot of epochs can cause overfitting of the training dataset, while too few might have the outcome of an underfit problem. Early stopping is a strategy that facilitates you to mention an arbitrary large number of training epochs and stop training after the model performance ceases improving on a hold out validation dataset.

With regards to sequential or time series data, conventional feedforward networks can’t be leveraged for learning and forecasting/prediction. A mechanism is needed that can retain historical data to predict the future values. Recurrent neural networks or RNNs in short are a variety of the traditional feedforward artificial neural networks that can handle sequential data and can be trained to retain the know-how, from a historical perspective.

The Generative Adversarial Network, or GAN for short, is an architecture for training of a generative model. The architecture is consisted of dual models. The generator that we are concerned with, and a discriminator model that is leveraged to help in the training of the generator. To start with, both of the generator and discriminator models were implemented as Multilayer Perceptrons (MLP), even though more lately, the models are implemented as deep convolutional neural networks.

Human activity recognition, or HAR in short, is a difficult time series classification activity. It consists of forecasting the movement of an individual on the basis of sensor information and conventionally consists of deep domain expertise and strategies that range from the raw data in order to go about fitting a machine learning model. Lately, deep learning strategies like convolutional neural networks and recurrent neural networks have demonstrated potent and even accomplish cutting-edge outcomes by automatically learning features from the

There are several perspectives on what the difference is between a vulnerability assessment versus a penetration test. The primary distinction, appears to be that many hold the belief a comprehensive penetration test consists of identification of as many vulnerabilities as feasible, while others hold the belief that Penetration Tests are objective-oriented and primarily don’t concern themselves with other vulnerabilities might exist.