Recommender systems are used in a variety of domains, from e-commerce to social media to offer personalized recommendations to customers. The benefit of recommendations for customers, such as reduced information overload, has been a hot topic of research. However, it's unclear how and to what extent recommender systems produce commercial value. It's challenging to create a reliable product suggestion system. However, defining what it means to be reliable is also a challenging task.
Python is one of the most widely used programming languages in the world, and for good reason. Because of its vast libraries and flexible structure, it's simple to learn, has consistent and easy-to-parse syntax, and is utilized for artificial intelligence applications. The platform's spectacular ascent has sparked a devoted community, fueled in no little part by its adoption by big companies such as DropBox, Reddit, and Instagram, to name a few. Check out this list of Python developers to follow if you're seeking Python programmers who are leading the charge. The people on this list have solid technical credentials, are constantly adding new and interesting features to the platform, and have a strong social media presence.
Although Artificial Intelligence, Machine Learning and Deep Learning are often used interchangeably, are they the same thing? Data science has become the new sensation in today's world. With copious amounts of data being generated daily, it only makes sense for companies to make use of the technologies to make appropriate analyses to make sound decisions. Whether it's a recommendation on Netflix, or Google Maps, or a Ride on Uber, there are a lot of benefits and convenience provided by these technologies. Companies can leverage these technologies to provide a better experience, maximize sales and profits if they can leverage the data and predict the consumer behaviour and purchasing pattern-The right way.
Think of all the data sources which include your personal information within the public administration services; be it bank account details, financial or medical records, tax information, etc. We often take it for granted that our data is safe and protected. However, what happens when this information is shared among different public administration entities? In reality, the General Data Protection Regulation (GDPR) laws safeguard the general public by limiting what data can be shared among entities, requiring that the data be anonymised before it is shared among different entities, including those within the public administration. The Multilingual Anonymisation for Public Administration (MAPA) Project is a European-funded project which is developing an open-source toolkit that enables effective and reliable text anonymisation, focusing on the medical and legal domains.
The rapid evolution of Technology is expanding and helps enable faster change and advancement in various fields, accelerating the rate of change to the point where it will eventually become exponential. However, it is not just technology trends and leading technologies that are changing; much more has changed this year due to the outbreak of COVID-19, which has caused IT workers to recognize that their jobs will not be the same in the contactless world. The Global pandemic has pushed digitization and automation, helping businesses thrive even in adversity. As a result, many companies are increasingly adopting disruptive technologies and changing their business strategies to sustain themselves. The impact of the pandemic will last a long time, and the digital shift will continue.
AI Researcher, Cognitive Technologist Inventor - AI Thinking, Think Chain Innovator - AIOT, XAI, Autonomous Cars, IIOT Founder Fisheyebox Spatial Computing Savant, Transformative Leader, Industry X.0 Practitioner The number of Internet of Things (IoT) devices worldwide is forecast to almost triple from 8.74 billion in 2020 to more than 25.4 billion IoT devices in 2030. In order to stabilize climate change, we need to hold Earth's temperature at 1.5 C above pre-industrial levels. This means we need to halve global greenhouse gas emissions by 2030 and reach net zero before 2050. On the frontline of digitalization lies 5G, itself an exponential technology, a platform enabling technologies such as #artificialintelligence (AI), blockchain, the internet of things (#IoT), quantum computing and extended reality (XR). The solutions are not hypothetical, they just need to be scaled up.
Chatbots have a checkered past of often not delivering the performance their providers have promised. This is especially true in the IT service management (ITSM) and multilingual NLP spaces, where service desks found support teams deluged with complaints -- yes, about the support chatbots. Just getting English language nuance right and how enterprises communicate often require chatbots to be custom programmed with constraint and logic workflows supported with natural language processing (NLP) and machine learning. If that sounds like a science project, it is, and IT users are the test subjects. Because of their complexity, chatbots were contributing to already overflowing trouble-ticket queues.
Children inevitably adapt to the culture in which they were raised. Parents or guardians shape the lens through which they view the world, largely through the examples they set. Many parents experience humored horror when a child picks up on an inappropriate word, likely from an overheard adult conversation, and begins to employ that expression in their everyday speech. It does not matter whether the parent is intentionally or unintentionally crafting the lens for the child -- they will still pick up on the parents' viewpoints and habits. We are witnessing this same progression in the tech world.
Autonomous self-driving cars have now become a trend in the world. There are big automakers and technology companies involved in the automation industry, but it is the start-ups that are making their place in the industry with new inventions. In a populous field of more than 300 start-ups in self-driving cars, let's take a closer look at the top autonomous self-driving car companies that have achieved unicorn status. Velodyne Lidar provides smart, powerful lidar solutions for autonomous vehicles, driver assistance, delivery solutions, robotics, navigation, mapping, and more. Headquartered in San Jose, Calif, Velodyne is known worldwide for its portfolio of breakthrough lidar sensor technologies.
I work in Machine Learning. To readers/viewers of my work, this won't come as a surprise. To people who don't know me as well, feel free to check out my LinkedIn/articles/videos for a better understanding of my skills/experience. My specialty is in statistical analysis. I've had experience working in Road Safety, Health System Analysis, Big Data Analysis for a Bank, disease detection, biometric recreation, and currently work in Supply Chain Analysis.