Introduction

I was formally (1998-2016) a Senior Research Fellow in the Institute of Educational Technology (IET) at the Open University (OU) in the UK.  It was in that context that I first started thinking about the potential of Learning Analytics in my field which is Accessibility of eLearning and Disabled Student Support.  Looking back through my work-related blog (…

When we take into account the insurance and banking industry, data plays a central role in it. Insurance is a people-centric business. A business that heavily relies on an individual’s data to the maximum extent possible. And the data Insurance providers and carriers have access to more of such data than ever before. The amount of data, we as humans have created in the past two years is simply unprecedented. …

Ever since the payment systems existed, there were always people who would find sophisticated ways to get to someone’s finances illegally. It has become a major problem in the modern era when all transactions can easily be completed online with only entering your credit card information. Even in the 2010s quite a lot of American retail website…

There are a lot of AI Companies that offer Machine Learning development. Even choosing the right ones for your project could take a decent amount of time, not even mentioning to pick the one that fits.

We decided to help CEOs, established companies, and startups that are looking for AI & ML Developer to save time…

By Stefan Stoyanov, Business Analytics & Research Intern at Boemska

I started my MSc Business Analytics course at theh University of Surrey almost one year ago. I had no prior experience in Machine Learning or data science. Before, I used to develop and manage EU projects…

In 1956, American Computer specialist John McCarthy created the Dartmouth Conference, at which the term Artificial Intelligence was first adopted. Researchers Allen Newell and Herbert Simon were instrumental in propelling AI as a field of software engineering that could…

Mobile health (mHealth) is considered one of the most transformative drivers for health informatics delivery of ubiquitous medical applications. Machine learning has proven to be a powerful tool in classifying medical images for detecting various diseases. However, supervised machine learning requires a large amount of data to train the model, whose storage and processing pose considerable system requirements challenges for mobile applications. Therefore, many studies focus on…

I have been frequently asked about the tools for the Machine Learnign projects There are lot of them on the market so in my newest post you will find my view on them. I would like to start my first Machine Learning project. But I do not have tools. What should I do? What are the tools I could use?

I will give you some hints and advices based on the toolbox I use. Of course there are more great tools but you should pick the ones you like. You should also use the tools that make your…

I have mentioned that every Machine Learning process is built from several steps like:

• what would you like to achieve (define the goal)
• prepare the data
• select an algorithm(s)
• build and train the model
• test the model (and score it)

Let’s review them one by one. I should mention that you will be able to find information over the internet that the number of steps is different from what you see on this blog. For example you can…

What is Machine Learning? This story started in mid 60 in the last century. Scientists and engineers found a lot of problems that were too complicated for traditional algorithms that it was not possible to create a program that could have possibly solved the problem.

Imagine a case where you have an object that is descirbed by 21 properties (as an input) and based on these properties you need to classify it to group A or to the group B. How would you solve the problem? Would you need…

As we all know that artificial Intelligence is slowly slowly becoming the most important and most integral part for the small to big businesses. It helps the business from the purchase of a product or manufactures the products to deliver the product to the client or customers. Here we have come with a small analysis of big business Company named coca…

The internet is evolving day by day, and when users shop online, they are flooded with thousands of results, leaving them in a dilemma to choose the best possible product that suits their requirements. Have you ever thought of how Google Ads precisely knew what you need and display…

When we look at broadly different kinds of Machine Learning that are used in practice in Artificial Intelligence

Historically, there have been several approaches in Machine learning for AI like supervised learning, unsupervised learning, reinforcement learning, case-based reasoning, inductive logic programming, experience based generalisation etc. there have been several examples of waves of machine learning for different AI problems. But, of them the 3 most important categories of…

A complete guide to K-means clustering algorithm

Everything you need to know about a top algorithm in Machine Learning

Introduction:

When dealing with building machine learning models, Data scientists spend most of the time on 2 main tasks when building machine learning models

Pre-processing and Cleaning

The major portion of time goes in to collecting, understanding, and analysing, cleaning the data and then building features. All the above steps mentioned are very important and critical to build successful machine learning…

Price errors and their impact:



Price errors are one of the ways in which revenue leakage occurs in e-commerce business. Although retailers put various checks and balances in place, pricing errors are still common. Data entry mistakes, misplaced decimal points, reversal of digits, and other clerical errors made in hurry are the major contributors. It can also occur because errors in feeding promotional offer dates. Promotions might unintendedly start early or end late. Such revenue…

What is Automated Machine Learning? Quite simply, it is the means by which your business can optimize resources, encourage collaboration and rapidly and dependably distribute data across the enterprise and use that data to predict, plan and achieve revenue goals.

With the right tools, today’s average business user can become a Citizen Data Scientist, using data integrated from various sources to learn, test theories and make decisions. AutoML comes into play as…

This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artifacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique…