Posts Tagged

Machine Learning

Data ScienceEventsMachine Learning

For people in the know, machine learning is old hat. Even so, it’s set to become the data buzzword of the year — for a rather mundane reason. When things get complex, people expect technology to ‘automagically’ solve the problem. Whether it’s automated financial product consultation or shopping in the supermarket of

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Data ScienceMachine LearningResources

The Estimators API in tf.contrib.learn (See tutorial here) is a very convenient way to get started using TensorFlow. The really cool thing from my perspective about the Estimators API is that using it is a very easy way to create distributed TensorFlow models. Many of the TensorFlow samples that you

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IndustryMachine Learning

As buzzwords become ubiquitous they become easier to tune out. We’ve finely honed this defense mechanism, for good purpose. It’s better to focus on what’s in front of us than the flavor of the week. CRISPR might change our lives, but knowing how it works doesn’t help you. VR could

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Artificial IntelligenceMachine Learning

According to the prediction of IDC Futurescapes, two-thirds of Global 2000 Enterprises CEOs will center their corporate strategy on digital transformation. A major part of the strategy should include machine learning (ML) solutions. The implementation of these solutions could change how these enterprises view customer value and internal operating model

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Artificial IntelligenceData ScienceMachine Learning

It is no doubt that the sub-field of machine learning / artificial intelligence has increasingly gained more popularity in the past couple of years. As Big Data is the hottest trend in the tech industry at the moment, machine learning is incredibly powerful to make predictions or calculated suggestions based

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Data ScienceData Science 101FeaturedMachine Learning

We hear the term “machine learning” a lot these days (usually in the context of predictive analysis and artificial intelligence), but machine learning has actually been a field of its own for several decades. Only recently have we been able to really take advantage of machine learning on a broad

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Artificial IntelligenceData ScienceMachine Learning

From Jeopardy winners and Go masters to infamous advertising-related racial profiling, it would seem we have entered an era in which artificial intelligence developments are rapidly accelerating. But a fully sentient being whose electronic “brain” can fully engage in complex cognitive tasks using fair moral judgement remains, for now, beyond

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Data ScienceFeaturedMachine LearningResourcesTopics

In the last few months, I have had several people contact me about their enthusiasm for venturing into the world of data science and using Machine Learning (ML) techniques to probe statistical regularities and build impeccable data-driven products. However, I’ve observed that some actually lack the necessary mathematical intuition and

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Artificial IntelligenceData ScienceEventsMachine LearningUnderstanding Big Data

Ajit Jaokar is a leading expert working at the intersection of Data Science, IoT, AI, Machine Learning, Big Data, Mobile, and Smart Cities. He teaches IoT and Data Science at Oxford and also is a director of Smart Cities Lab in Madrid. Ajit’s work involves applying machine learning techniques to

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Artificial IntelligenceData ScienceMachine Learning

From Decentralized Model Exchanges to Model Audit Trails [This is based on a talk I first gave on Nov 7, 2016. Here are the slides.] In recent years, AI (artificial intelligence) researchers have finally cracked problems that they’ve worked on for decades, from Go to human-level speech recognition. A key

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