Python's popularity is growing tremendously and it's becoming more and more relevant economically and technologically. In this 7 in 1 version you get a full collection of The Python Bible series. From the first volume on, you will be lead on a structured way to the mastery of Python. Besides the basics and the intermediate concepts, you will also learn how to apply it in areas like machine learning, financial analysis and neural networks. At the end you will additionally be introduced to one of the most interesting fields of computer science, which is computer vision After reading this collection, you will not only understand the programming language but you will also be able to work on projects in the stated fields.

The use of artificial intelligence (AI) is nothing new in health care applications. AI can be seen in robotic surgeries, image and data analysis, automation of administrative tasks, and assisting clinical diagnostics. The use of this technology is helping providers offer faster service, more accurately diagnose diseases, and analyze data to identify trends or genetic information. We are now seeing these tools expand beyond the typical hospital or primary care setting to include health care providers like dentists to create a new standard of care, improve business operations, and support public health research in dentistry. I sat down with Florian Hillen, Founder and CEO of VideaHealth, an AI and machine learning company created to improve the delivery of health care services for dentistry, to hear more about how AI is impacting this field of medicine.

Relation extraction (RE) is one of the most important tasks in information extraction, as it provides essential information for many NLP applications. In this paper, we propose a cross-lingual RE approach that does not require any human annotation in a target language or any cross-lingual resources. Building upon unsupervised cross-lingual representation learning frameworks, we develop several deep Transformer based RE models with a novel encoding scheme that can effectively encode both entity location and entity type information. Our RE models, when trained with English data, outperform several deep neural network based English RE models. More importantly, our models can be applied to perform zero-shot cross-lingual RE, achieving the state-of-the-art cross-lingual RE performance on two datasets (68-89% of the accuracy of the supervised target-language RE model). The high cross-lingual transfer efficiency without requiring additional training data or cross-lingual resources shows that our RE models are especially useful for low-resource languages.

In recent news, AI didn't come off very well. Companies like IBM or Microsoft just announced that they will end the sales of facial recognition technology, one area of AI, with immediate effect. The real-life implications might be devastating: Whereas the technology might be well-trained to identify white faces, it fails to differentiate black faces. When used by law enforcement, this could lead to false accusations for People of Color. Critical press coverage, intransparency and unethical business practices have led to distrust regarding emerging technologies around the world.

As summer approaches, more people are opting to enjoy the sunshine by riding their bikes. Josh Andres, an IBM Researcher who regularly rides his bike, was inspired by the frustration experienced by bike riders when getting stuck at a red traffic light. This problem aligned well with his research and that of his collaborators at the RMIT Exertion Games Lab, which looks to study how humans can partner with intelligent like systems. Their collaboration resulted in the development of'Ari', a Smart e-Bike which can extend the rider's physical and cognitive abilities to catch traffic lights on the green. Ari used artificial intelligence (AI) and the Internet of Things to assist the rider to regulate the speed and cross-traffic lights on green.

Artificial intelligence will create new liabilities for organizations, but it can also be harnessed as a risk management tool, a panel of experts said. By processing high volumes of data, risk managers can get a better grasp of the risks they face, spend less time on repetitive tasks and use connected devices to enhance their risk management processes, they said. Companies are already implementing AI, and risk managers should ensure they are aware of the risks and liabilities that the technology creates, said Philippe Cotelle, head of insurance and risk management at Airbus Defence & Space, a division of Airbus SE in Toulouse, France. He was speaking during a session of the Federation of European Risk Management Associations' biennial forum in Berlin on Monday. Risk managers should make sure they are "going to capture what is within AI both in terms of risks and in terms of opportunity, and it becomes a tool for the risk manager," Mr. Cotelle said.

A car which can climb walls and step over holes thanks to its robotic legs could transform the way rescue teams operate in disaster zones. More than 10,000 people died in natural catastrophes in 2017, with an estimated 201 million needing international humanitarian assistance. One of the problems is reaching those affected. Car maker Hyundai has unveiled a concept vehicle named Elevate which blends the technology found in electric cars with that found in robots to help it cover terrain beyond the limitations of even the most capable off-road vehicle. Elevate can be driven by first responders to a location like a traditional electric car. But when the terrain gets tough, it can use its "highly dexterous" robotic legs to move in any direction.