If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
A few short years ago, personal digital assistants like Amazon's Alexa, Apple's Siri, and Google Assistant sounded futuristic. Now, the future is here and this future is embedded, augmented, and ubiquitous. Digital assistants can be found in your office, home, car, hotel, phone, and many other places. They have recently undergone a massive transformation and run on operating systems that are fueled by artificial intelligence (A.I.). They observe and collect data in real-time and have the capability to pull information from different sources such as smart devices and cloud services and put the information into context using A.I. to make sense of the situation.
With the vast amounts of research and development occurring every day in Machine Learning, it can be challenging for industry professionals solving real-life use-cases and academic researchers to keep up with all the recent innovations in their specific field of interest. Having struggled for a long time, after a series of exploration, I finally stumbled upon a handful of resources that I wish to share in this post. The list I am proposing here is not exhaustive. However, I am sure they will be sufficient to keep you updated-- eliminating all the heavy lifting of scanning the list of published papers yourself. The resources I will discuss in this post encompass video, newsletter, and podcast formats.
"If we really want to build a machine on the verge of human-level intelligence, we need to ditch current statistical and data-driven learning paradigm in favour of a causal-based approach." In the 1970s and early 1980s, computer scientists believed that the manipulation of symbols provided a priori by humans was sufficient for computer systems to exhibit intelligence and solve seemingly hard problems. This hypothesis came to be known as the symbol-rule hypothesis. However, despite some initial encouraging progress, such as computer chess and theorem proving, it soon became apparent that rule-based systems could not solve problems that appear seemingly simple to humans. "It is comparatively easy to make computers exhibit adult level performance […] and difficult or impossible to give them the skills of a one-year-old".
AlphaFold, DeepMind's protein structure program, is impressive because it reveals so much fundamental information about living organisms. Proteins are the building blocks of life, after all, and as such they are essential to life and to the development of medicines. Proteins can be drug targets, and they can themselves be drugs. In either case, it is important to know the intricate ways in which they fold into various shapes. Their coils, floppy bits, hidden pockets and sticky patches can control, for example, when a signal is sent between cells or if a process is turned on or off.
Tech conferences are becoming one of the most attractive venues to learn about the latest innovations in emerging sectors, including artificial intelligence, web3, AR/VR, IoT, and the metaverse. In particular, this year's data conferences are a good place to look for the most interesting trends. Take a look at the most notable data-focused B2B events in the second half of 2022. Big data, public web data gathering, and AI are the three pillars of this year's conferences bringing together mid- and upper-level data enthusiasts to share experiences and jointly find a pathway to a more structured digital future. OxyCon, the most prominent event in the world of web scraping, returns for the third time, attracting thousands of registered participants.
Amazon, Google, and Microsoft are three tech giants who have pioneered machine learning in their offerings. All three of them have cloud platforms that help other companies and individual users make the most of machine learning. At my current work, we use Microsoft Azure as our production environment. Similarly, most companies use either one of these platforms. Their platforms are the closest available resources to real-world production environments.
Udemy is the biggest website in the world that offer courses in many categories, all the skills that you would be looking for are offered in Udemy, including languages, design, marketing and a lot of other categories, so when you ever want to buy a courses and pay for a new skills, Udemy would be the best forum for you. You can find payment courses, 100 free courses and coupons also, more than 12 categories are offered, and that what makes sure you will find the domain and the skill you are looking for. Our duty is to search for 100 off courses and free coupons. This Qlik AutoML Course will help you to become a Machine Learning Expert and will enhance your skills by offering you comprehensive knowledge, and the required hands-on experience on this newly launched Cloud based ML tool, by solving real-time industry-based projects, without needing any complex coding expertise. Most Importantly, Guidance is offered beyond the Tool – You will not only learn the Software, but important Machine Learning principles.
Then, we calculate the ratio of the weighted sum of the squares of the differences between each category's average and overall average to the sum of squares between each value and overall average. The range of eta is between 0 and 1. A value closer to 0 indicates all categories have similar values, and any single category doesn't have more influence on variable y. A value closer to 1 indicates one or more categories have different values than other categories and have more influence on variable y. Eta can be used in EDA and data processing to know which categorical features are more important in machine learning model building.
This week's list of top data news highlights covers July 30, 2022 to August 5, 2022 and includes articles on practicing complex surgeries with virtual reality and using an AI system to create an advertising campaign. India's National Tiger Conservation Authority (NCTA) has used over 26,000 cameras to capture over 24 million images of tigers around the country. Conservationists are using an AI system to identify tigers found in the images and quantify the total tiger population in the country. The NCTA plans to use an AI system to map patrol routes throughout sanctuaries to better monitor tigers next. Researchers at the University of New Orleans, Louisiana Department of Environmental Quality, and Jefferson Parish Department of Environmental Affairs have used a supercomputer to simulate the diffusion and dispersion of chemical compounds that can deodorize a landfill.
China's export growth continued to rise in July, sending trade surplus to a record high, according to government data. China's exports grew 18% to $333 billion compared to the same period last year, and were up from 17.9% in June, according to data from China's customs. Imports, however, remained soft, growing 2.3% in July compared to a year ago. That was lower that economists' estimates of 4%, and suggests weak domestic demand amid lockdowns across the country as China attempts to stem the outbreak of COVID-19. China's total trade surplus reached an all-time high of $101.3 billion in July, breaking the record set in June.