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Feature Engineering for Automated Machine Learning

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One of the biggest challenges in machine learning workflows is identifying which inputs in your data will provide the best signals for training predictive models. For image data and other unstructured formats, deep learning models are showing large improvements over prior approaches, but for data already in structured formats, the benefits are less obvious. At Zynga, I've been exploring feature generation methods for shallow learning problems, where our data is already in a structured format, and the challenge is to translate thousands of records per user into single records that summarize user activity. Once you have the ability to translate raw tracking events into user summaries, you can apply a variety of supervised and unsupervised learning methods to your application. I've been leveraging the Featuretools library to significantly reduce my time spent building predictive models, and it's unlocked a new class of problems that data scientists can address.


Top Website & App Development Company - Webgen Technologies

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Powerful and process based applications for all types of industries and businesses. Custom apps and websites that serve the travel industry. Search Engine Optimization, Search Engine Marketing, Social Media Optimization, Online Reputation Management and building targeted campaigns. Chatbots like Facebook Messenger, Slack Bot as well as Gambling bot and other kinds to help you with task automation.


Top Website & App Development Company - Webgen Technologies

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Powerful and process based applications for all types of industries and businesses. Custom apps and websites that serve the travel industry. Search Engine Optimization, Search Engine Marketing, Social Media Optimization, Online Reputation Management and building targeted campaigns. Chatbots like Facebook Messenger, Slack Bot as well as Gambling bot and other kinds to help you with task automation.


TTH - Tech update on Mobiles, AI, Laptops, Gadgets, Robotics, UAV & More

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GitHub today launched GitHub Security Lab, an ongoing effort to protect open source projects. The GitHub Security Lab aims to bring together security researchers from partner organizations such as Google, Microsoft, Mozilla, Oracle, Uber and HackerOne. To boost the GitHub Security Lab, GitHub is CodeQL, an open source variant analysis software from Semmle, a company that it acquired in September to help GitHub better detect vulnerabilities in the code. Semmle security software is used by companies such as Google, Microsoft and NASA. GitHub says it has used the CodeQL semantic code analysis engine to find more than 100 vulnerabilities in popular open source projects with custom queries.


TTH - Tech update on Mobiles, AI, Laptops, Gadgets, Robotics, UAV & More

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Google Cloud is making Contact Center AI generally available for use today. The cloud service is built with Dialogflow of the conversational AI engine to automate interactions with customers in call centers. Contact Center AI contains Virtual Agent to automatically respond to customer inquiries with voice or text or transfer the conversation to a person when a bot cannot help a client. Agent Assist uses natural language processing to increase customer service agent interactions with customers when a bot cannot help a client. The news comes today when Google launched its rich communication services (RCS) to Android message users in the United States, and days after Google's experimental unit, the Area 120 CallJoy service to answer phone calls and questions Small business customers get an update.


Singapore rolls out national strategy on artificial intelligence for 'impactful' social, economic benefits

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SINGAPORE: By 2022, people living in Singapore will be able to report municipal issues via a chatbot that asks for details in real time and automatically identifies the correct government agency in charge. This will be made possible by artificial intelligence (AI), which is also set to power a tool that helps in the detection of diabetic eye disease and an automated marking system for English in primary and secondary education by the same year. More initiatives tapping on AI technologies, such as machine learning and computer vision, are in the pipeline over the next decade, according to five projects unveiled on Wednesday (Nov 13) as part of Singapore's new "National AI Strategy". The new strategy, which maps out how Singapore will develop and use AI to transform the economy and improve peoples' lives, was announced by Deputy Prime Minister Heng Swee Keat at the final day of the "Singapore FinTech Festival (SFF) x the Singapore Week of Innovation and TeCHnology (SWITCH) Conference". Describing it as the next step in Singapore's Smart Nation Journey, Mr Heng said: "Countries will need to keep pace with technology, and harness it to tackle common challenges and national priorities."


Intelligent Automation and Human-Machine Collaboration

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When people encounter something new, it's human nature to compare it to things we already know. But executives seeking to adopt intelligent automation may struggle to realize its benefits if they don't consciously set aside a few pre-existing beliefs. The Age of With requires thinking beyond bots--it's the future of human-AI interaction. The first belief to shed is that intelligent automation is just like conventional software. Adopting digital workforce management and treating digital workers as a part of the workforce--not software applications or outsourced functions--can put organizations squarely on the path to enhancing human judgement and human-machine collaboration and delivering actionable insights.


Intelligent Automation and Human-Machine Collaboration

#artificialintelligence

When people encounter something new, it's human nature to compare it to things we already know. But executives seeking to adopt intelligent automation may struggle to realize its benefits if they don't consciously set aside a few pre-existing beliefs. The Age of With requires thinking beyond bots--it's the future of human-AI interaction. The first belief to shed is that intelligent automation is just like conventional software. Adopting digital workforce management and treating digital workers as a part of the workforce--not software applications or outsourced functions--can put organizations squarely on the path to enhancing human judgement and human-machine collaboration and delivering actionable insights.


TTH - Tech update on Mobiles, AI, Laptops, Gadgets, Robotics, UAV & More

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Have you ever wondered how to pronounce a particularly challenging word? Google announced that it will launch a tool in mobile search that allows you to practice pronunciations without leaving the results page. Coinciding with its debut, the tech giant this morning added images to its search dictionary and translation features aimed at helping to better communicate the meaning of the words. The pronunciation module, which is released today in American English, and Spanish will soon follow, allows you to practice saying specific words to your phone's microphone. You will receive comments on what you can adjust in your pronunciation, in any case.


Machine Learning & AI

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Thanks to better instruments, including technologies developed at the Lab, we can see things at a microscopic and atomic scale. We can measure vibrations imperceptible to the human eye and capture high-resolution images of objects millions of light years away. But those instruments produce vastly larger datasets than ever. The Large Synoptic Survey Telescope (LSST) will produce 20 terabytes of data every night, about 60 petabytes over its lifetime. The Large Hadron Collider will have even more, with 50 petabytes in 2018 alone and 500 petabytes by 2024 (not including the 900 petabytes from past experiments).