From exploratory data analysis to automated machine learning, look to these techniques to get your data science project moving - and to build better models
"Do you need to classify data or predict outcomes? Are you having trouble getting your machine learning project off the ground? There are a number of techniques available to help you achieve lift-off.
Some of the eight methods discussed below will accelerate your machine learning process dramatically, while others will not only accelerate the process but also help you build a better model. Not all of these methods will be suitable for a given project, but the first one-exploratory data analysis-should never be left out..."
The rise of precision medicine is being augmented by greater use of deep learning technologies that provide predictive analytics for earlier diagnosis of a range of debilitating diseases
"The latest example comes from researchers at Michigan-based Beaumont Health who used deep learning to analyze genomic DNA. The resulting simple blood test could be used to detect earlier onset of Alzheimer's disease.
In a study published this week in the peer-reviewed scientific journal PLOS ONE, the researchers said their analysis discovered 152 'significant' genetic differences among Alzheimer's and healthy patients. Those biomarkers could be used to provide diagnoses before Alzheimer's symptoms develop and a patient's brain is irreversibly damaged..."
Is AI reshaping the digital marketing industry? Yes! In recent years, Artificial Intelligence (AI) has become a vital entity in the realms of digital marketing, with digital marketers across the globe leveraging AI to streamline and optimize digital marketing campaigns and gain client loyalty in the digital age
"For most people, AI seems more of a science myth than a fact. However, the truth is that AI is no longer a far-fetched concept, and it's already reshaping the digital marketing industry. In fact, it's projected that by the end of 2021; companies would be spending at least $57 billion on AI platforms and associated technologies.
By allowing enterprises to efficiently collect data, analyze it, apply it, and then learn from it, AI is reshaping digital marketing strategies. From Apple's Siri to Alibaba's FashionAI, more and more organizations are implementing AI in their digital marketing operations. AI is definitely changing the future of digital marketing-here's how..."
The steady rise of AI and machine learning is providing organizations with enormous value-helping to make sense of massive data sets, and find patterns that can automate programs across industries
"AI can help companies create a seamless, personalized, and responsive experience for consumers- whether they are shopping for the holiday, saving for college, or considering a new car. Done right, AI can help companies identify, reach, and convert their target audiences in the right place, at the right time, with the right message. But done wrong, there can be unintended consequences.
The value of AI and automation is only as good as the underlying data sets that drive its algorithms. The complexity of AI means that there's often little visibility into why and how data was interpreted. At best, flawed data will hamper the success of AI-powered programs, sending your message to uninterested consumers, or not generating a promised boost to sales or cost savings. At worst, the results can be more questionable, creating the potential for bias, and undermining desired objectives and results..."
The new technology can take partial information and produce intelligent inferences, according to new research from Cambridge Quantum Computing
"As artificial intelligence and machine learning algorithms have received attention for making accurate predictions--in everything from judging the outcome of human rights trials to predicting the winner of the Kentucky Derby to identifying cancer--another new technology has now been applied to the task of reasoning: quantum computing.
In a new paper, scientists at Cambridge Quantum Computing exhibited how quantum computing, still a nascent field, can be useful in making practical decisions. The aim, according to the head of the Quantum Machine Learning division of CQC, Mattia Fiorentini, was to show that quantum computers can handle intuitive reasoning--using inference on a probability model--which hadn't been approached this way before.."
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