algorithm


Explainable AI or Halting Faulty Models ahead of Disaster

#artificialintelligence

Experienced machine learning experts will know about the challenge's complexity and rightfully question the results' validity. At the same time, submissions like this Notebook illustrate how the Titanic competition's leaderboard can be forged effortlessly; A top-performing model can be created by collecting and including the publicly accessible list of survivors. Clearly, such overfit models only work for one very specific use case and are virtually useless for predicting outcomes in any other situation (not to mention the ethics of cheating). So, how can we make sure we have trained or are provided with a model that we can actually use in production? How can machine learning systems be deployed without likely ensuing disaster?


Machine Learning In Healthcare: All You Need To Know Robots.net

#artificialintelligence

If you want to get into your doctor's bad books, turn up to your next appointment having preemptively diagnosed yourself via Google. If there's one thing that annoys healthcare professionals, it's patients thinking that computers can do their job as well as them. Some physicians even have signages in their waiting rooms stating that. Algorithms aren't going to replace our doctor any time soon. However, there's a lot of machine learning in healthcare that can help him diagnose you faster and more efficiently.


Better Ways to Predict Who's Going to Quit

#artificialintelligence

Companies know that employee turnover is expensive and disruptive. And they know that retaining their best and brightest employees helps them not only save money but also preserve competitive advantages and protect intellectual capital. Most retention efforts, however, rely on two retrospective tools. First, exit interviews are conducted to better understand why people chose to leave, though by this point, it is usually too late to keep them. Second, annual employee surveys are used to assess engagement.


Neural Networks: Feedforward and Backpropagation Explained

#artificialintelligence

Mathematically, this is why we need to understand partial derivatives, since they allow us to compute the relationship between components of the neural network and the cost function. And as should be obvious, we want to minimize the cost function. When we know what affects it, we can effectively change the relevant weights and biases to minimize the cost function. If you are not a math student or have not studied calculus, this is not at all clear. So let me try to make it more clear. The squished'd' is the partial derivative sign.


The 4 Most Important Traits to Look for When Hiring an AI Expert

#artificialintelligence

But don't forget to consider the soft skills, too. After all, this person will be playing an important role as a team player -- both now and in the future.


Artificial Intelligence in eCommerce – Infographic

#artificialintelligence

Artificial intelligence (AI) is a science that deals with building intelligent machines and algorithms that can think and respond like a human (that is learning according to human). Artificial intelligence has filled the digital lacuna and summoned reality into utopia. Undoubtedly it has filled every walk of life from airport to home automation and e-commerce is no new story for its ink. It won't be necromancy to add that not only Artificial intelligence is simplifying the E-commerce but also providing unbelievable new horizon for its growth. With every new artificial add on ads to new possibility and a wow factor to E-commerce let us look few of the Artificial intelligence, which is changing the E-commerce spectrum.


How data can predict which employees are about to quit: Rather than relying on exit interviews and their comparisons to occasional employee surveys to determine engagement, organizations can turn instead to big data and advanced analytics to identify those workers at greatest risk of quitting.

#artificialintelligence

Rather than relying on exit interviews and their comparisons to occasional employee surveys to determine engagement, organizations can turn instead to big data and advanced analytics to identify those workers at greatest risk of quitting. A new Harvard Business Review article outlines how applying machine learning algorithms to turnover data and employee information can provide a much more accurate picture of workplace satisfaction. This measure of "turnover propensity" comprised two main indicators: turnover shocks, which are organizational and personal events that cause workers to reconsider their jobs, and job embeddedness, which describes an employee's social ties in their workplace and interest in the work they do. Though achieving this kind of "proactive anticipation" will require a sizable investment of time and effort to develop the necessary data and algorithms, the payoff will likely be worth it: "Leaders can proactively engage valued employees at risk of leaving through interviews, to better understand how the firm can increase the odds that they stay," per HBR. More articles on leadership and management: Can your anesthesia department handle NORA?


Ethics and artificial intelligence Bruegel

#artificialintelligence

Machine learning and artificial intelligence (AI) systems are rapidly being adopted across the economy and society. These AI algorithms, many of which process fast-growing datasets, are increasingly used to deliver personalised, interactive, 'smart' goods and services that affect everything from how banks provide advice to how chairs and buildings are designed. There is no doubt that AI has a huge potential to facilitate and enhance a large number of human activities and that it will provide new and exciting insights into human behaviour and cognition. The further development of AI will boost the rise of new and innovative enterprises, will result in promising new services and products in – for instance – transportation, health care, education and the home environment. They may transform, and even disrupt, the way public and private organisations currently work and the way our everyday social interactions take place.


Data Science, the Good, the Bad, and the… Future

#artificialintelligence

How often do you think you're touched by data science in some form or another? Finding your way to this article likely involved a whole bunch of data science (whooaa). To simplify things a bit, I'll explain what data science means to me. "Data Science is the art of applying scientific methods of analysis to any kind of data so that we can unlock important information." If we unpack that, all data science really means is to answer questions by using math and science to go through data that's too much for our brains to process.


Data Science, the Good, the Bad, and the… Future - Knowlab

#artificialintelligence

How often do you think you're touched by data science in some form or another? Finding your way to this article likely involved a whole bunch of data science (whooaa). To simplify things a bit, I'll explain what data science means to me. "Data Science is the art of applying scientific methods of analysis to any kind of data so that we can unlock important information." If we unpack that, all data science really means is to answer questions by using math and science to go through data that's too much for our brains to process.