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The Advent of Ethical Artificial Intelligence in the Healthcare Industry

Introduction

As with any other industry, life sciences and healthcare is a big market of technology, especially the most talked-about technologies these days. Any guesses? Obviously, artificial intelligence and machine learning. Whether it is machine learning to help with automation tools or diagnoses, artificial intelligence plays an essential role in streamlining medical processes so the physicians can focus on what’s more crucial: helping the patient. 

A recent survey by Software Advice depicts a vast amount of patients who trust AI applications in healthcare. 

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How AI Is Revolutionizing the Retail Customer Experience

Artificial intelligence is here and is already having an impact in many industries. According to IDC, global spending on artificial intelligence systems is forecast to reach €31 billion in 2019, a 44% increase from 2018 spending. For any business that hasn't started its AI journey, it's time to look into the opportunities it provides.

This is because AI is revolutionizing every industry and sector, including the retail customer experience. Still, a lot of people are still not aware of the effects of AI or do not understand the scope of its applications. From helping customers find items through visual search to customizing their entertainment experience through chatbots, AI is revolutionizing the retail industry in a number of ways.

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Online Machine Learning: Into the Deep

Introduction

Online Learning is a branch of Machine Learning that has obtained a significant interest in recent years thanks to its peculiarities that perfectly fit numerous kinds of tasks in today’s world. Let’s dive deeper into this topic.

What Exactly Is Online Learning?

In traditional machine learning, often called batch learning, the training data is first gathered in its entirety and then a chosen machine learning model is trained on said data: the resulting model is then deployed to make predictions on new unseen data. 

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AI Is Booming Vaccine Supply Chain—From Blockchain To Big Data

COVID-19 cases are increasing at an astonishing rate around the globe. 96.2 million cases have occurred globally, out of which 2.06 million people have died. This immense rate of patient’s data production has paved the way for new innovative data storage technologies. This data is utilized afterward to predict and analyze pandemic measures to fight post-pandemic virus conditions. 

According to a study,  ISARIC4C is collecting data of patients who are suffering from the COVID-19 pandemic from over 250 hospitals in the United Kingdom. Big data is an innovative technology that can be utilized by health care centers to store an enormous amount of patient information. This helps in developing a better understanding of the nature of this virus, and this collected information can also be further utilized for future prevention methods. This technology helps in storing all sorts of data i.e. the infected, recovered, and the number of deceased people. Prediction models have been developed by researchers which need to be fed a lot of data. The 4C deterioration model is designed using ISARIC4C data to predict the risk of COVID-19. 

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The Convergence of Blockchain and Artificial Intelligence

Introduction

According to a 2016 research by Mckinsey, it was revealed that the total annual external investment in AI ranged between $8billion to $12billion in. Statistically, this is a clear sign that AI is making a great impact in the global industries especially the financial sector. In other words, it’s a revolutionary impact in the financial industry can not be underestimated.

Blockchain, on the other hand, has also shown its immense potential in so many industries especially in the finance industry. In fact, it’s digital disruption is greatly impacting how so many businesses operate in our contemporary world. While so many industries are beginning to embrace the amazing options these technologies – Artificial intelligence and Blockchain technology offer – helping them to create more value,  boosting sales, and so on,  it’s interesting to know that the combination of both will positively revolutionize the future of the fintech industry.

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Getting Started With Machine Learning Using Python

What Is Machine Learning?

Machine learning is a part of Artificial Intelligence that enables computers to learn automatically and improve themselves through experience. The primary focus of machine learning is to develop computer programs that could improve themselves according to the newly discovered data without being explicitly programmed. It predicts an output by combining data with statistical tools. It is also related to data mining and Bayesian predictive modeling. 

A system receives data as input and uses the algorithm to provide an output. The machine learning is used to fraud detection, portfolio optimization, predictive maintenance, and so on. There are several machine learning algorithms such as Naive Bayes, Decision trees, Support vector machine, K-nearest neighbor, K-means clustering, Random forest, etc. Today, it is being used in price prediction, self-driving cars, fraud detection, and even natural language processing.

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Modern Functional Test Automation Through Visual AI

Which looks better, #1 or #2?
"I am confident that once you give this functional test automation approach a try, you will rethink your entire current code-based approach." — Raja Rao, Head of Test Automation University

In this webinar, you'll see the modern, intelligent way of doing web and mobile testing. Specifically, functional, end-to-end UI testing.

The analogy is a gasoline car versus an electric car: both are cars, both need tires, seats, breaks, etc... but the core engine that moves the car is different - which makes a huge difference.