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Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importan

START, the world's first Web-based question answering system, has been on-line and continuously operating since December, 1993. It has been developed by Boris Katz and his associates of the InfoLab Group at the MIT Computer Science and Artificial Intelligence Laboratory. Unlike information retrieval systems (e.g., search engines), START aims to supply users with "just the right information," instead of merely providing a list of hits. Currently, the system can answer millions of English questions about places (e.g., cities, countries, lakes, coordinates, weather, maps, demographics, political and economic systems), movies (e.g., titles, actors, directors), people (e.g., birth dates, biographies), dictionary definitions, and much, much more. Below is a list of some of the things START knows about, with example questions. You can type your question above or select from the following examples.

Artificial intelligence (AI) is a branch of computer science that deals with intelligent behavior, learning, and adaptation in machines. Research in AI is concerned with producing machines to automate tasks requiring intelligent behavior.

Ai Research is a leading artificial intelligence research project. At Ai, we're creating a new form of life. Our expanding web site is an essential part of the emerging global discussion about artificial intelligence. On this website, we showcase the state of the art in pattern-matching conversational machines, demonstrated by Alan, and in reinforcement learning algorithms, demonstrated by HAL. Use our forums, original papers, online labs, demos and links to explore what's happening both at Ai (the project) and in AI (the field).

As a subset, Machine Learning focuses on growing from observations and experiences. The popularity of machine learning certification courses on online training platforms indicates that this is the thing of the future. Coming to R, it is one of the major languages for data science because of its excellent visualization features, a growing ecosystem of third-party packages, and tools for machine learning interpretability. R has emerged as a fantastic tool for scientific computing and has powerful statistical libraries. Beginners commonly use R for exploring the data before applying any automated learning.

"START, the world's first Web-based question answering system, has been on-line and continuously operating since December, 1993. It has been developed by Boris Katz and his associates of the InfoLab Group at the MIT Computer Science and Artificial Intelligence Laboratory. "

"Google Colaboratory Colab is a hosted Jupyter Notebook service that requires no setup to use and provides free access to computing resources, including GPUs and TPUs. Colab is especially well suited to machine learning, data science, and education."

"Artificial Intelligence (AI) is a field which combines computer science and robust datasets to enable problem-solving. It also encompasses sub-fields of machine learning and deep learning."

The Artificial Intelligence (AI) program at the University of Michigan comprises a multidisciplinary group of researchers conducting   theoretical, experimental, and applied investigations of intelligent systems. Current projects include research in rational decision   making, computational game theory, distributed systems of multiple agents, reinforcement learning, machine learning, cognitive modeling,   natural language processing, information retrieval, and robotics.

"Google's researchers have achieved a big breakthrough in quantum computing known as quantum supremacy. "

'A Platform for the Decentralized AI Economy. The free and open market for AI technologies, built on smart contracts. Create, combine and monetize AI technologies at scale.'

"City.AI has the goal to discuss trends and activities on how to apply AI in products and businesses among startups, developers, corporates, investors and research. Check whether City AI is active in your city above or get in touch with us!"

"We're proud that our work is helping to advance the field of AI research, far beyond DeepMind alone. As well as publishing research papers and collaborating with academia, we also release open source environments, datasets and code to support and accelerate research in the wider AI community. "

"Keep up with the latest information about Artificial Intelligence from the News, Publications, and Conferences - sponsored by AAAI, powered by AI technology."

"The GLTR demo enables forensic inspection of the visual footprint of a language model on input text to detect whether a text could be real or fake. It is a collaborative effort between Hendrik Strobelt, Sebastian Gehrmann, and Alexander Rush from the MIT-IBM Watson AI lab and Harvard NLP."

"We introduce GLTR to inspect the visual footprint of automatically generated tex. It enables a forensic analysis of how likely an automatic system generated a text."

The Neuromorphics Lab studies biological intelligence and embeds the derived fundamental principles in bio-inspired computers and robots.

"Introducing A.I. Experiments. Explore machine learning by playing with pictures, language, music, code, and more."

"The Berkeley Artificial Intelligence Research (BAIR) Lab brings together UC Berkeley researchers across the areas of computer vision, machine learning, natural language processing, planning, and robotics. BAIR includes over two dozen faculty and more than a hundred graduate students pursuing research on fundamental advances in the above areas as well as cross-cutting themes including multi-modal deep learning, human-compatible AI, and connecting AI with other scientific disciplines and the humanities."