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The 7 Steps of the Data Science Lifecycle - Applying AI in Business

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AI is not IT- and adopting artificial intelligence is almost nothing like adopting traditional software solutions. While software is deterministic, AI is probabilistic. The process of coaxing value from data with algorithms is a challenging and often time-consuming one. While non-technical AI project leaders and executives don't need to know how to clean data, write Python, or adjust for algorithmic drift – but they do have to understand the experimental process that subject-matter experts and data scientists go through to find value in data. Last week we covered the three phases of AI deployment, and this week we'll dive deeper in the seven steps of the data science lifecycle itself – and the aspects of the process that non-technical project leaders should understand.


Understanding the Power of Product Recommendation Engines

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According to a Forbes Survey from last year, 70 percent of buying decisions are influenced by how clients feel they are being treated; therefore, a superior personalized customer experience can go a long way towards increasing sales. Personalization requires the right product or service to be offered to the customer at the right moment and at the right price. With a plethora of product and service suites available, customers often defer to the expertise of the business to recommend the right solution for them. Businesses that can predict customer needs and supply effective solutions can ensure that their client base is always satisfied. The adage "the early bird gets the worm" has never been so true.


Product Search Engines - vs - Product Recommendation Engines

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However similar they may seem in terms of underlying technology, conventional search engines are quite different from product recommendation engines. Behaviour is typically at the center of a recommender system, while it is an added dimension for the search engine.


Top-10 Artificial Intelligence Startups in Hong Kong - Nanalyze

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Hong Kong has a very special place in our hearts. It's the safest place on the planet, with beautiful local people who are shy and endearing, who harbor a fondness for taking pictures of their food, who believe in ghosts, who despise "those uncouth mainlanders", and who invent some strange cartoon characters – like McDull the pig and his friend Excreman that's literally a turd that crawled out of the toilet. If you're someone who noticeably speaks English, don't expect the Hong Kong police to ticket you for jaywalking. They're too shy about their English to approach you. Of course these are the same people who won't hesitate to tell you that you look fat when you return from holiday.


Product recommendations in Digital Age

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Then came eBay and Amazon in 1995....... Amazon started as bookstore and eBay as marketplace for sale of goods. Since then, as Digital tsunami flooded, there are tons of websites selling everything on web but these two are still going great because of their product recommendations. We as customers, love that personal touch and feeling special, whether it's being greeted by name when we walk into the store, a shop owner remembering our birthday, helping us personally to bays where products are kept, or being able to customize a website to our needs. It can make us feel like we are single most important customer. But in an online world, there is no Bob or Sandra to guide you through the product you may like.