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The quest for high-quality data

O'Reilly on Data

As model building become easier, the problem of high-quality data becomes more evident than ever. Even with advances in building robust models, the reality is that noisy data and incomplete data remain the biggest hurdles to effective end-to-end solutions. Data integration and cleaning.

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15 best data science bootcamps for boosting your career

CIO Business Intelligence

An education in data science can help you land a job as a data analyst , data engineer , data architect , or data scientist. The course includes instruction in statistics, machine learning, natural language processing, deep learning, Python, and R. Remote courses are also available.

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Top Data Science Tools That Will Empower Your Data Exploration Processes

datapine

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations.

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Bringing an AI Product to Market

O'Reilly on Data

This tradeoff between impact and development difficulty is particularly relevant for products based on deep learning: breakthroughs often lead to unique, defensible, and highly lucrative products, but investing in products with a high chance of failure is an obvious risk. Prototypes and Data Product MVPs.

Marketing 362
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Augmented Analytics: Empowering Users with Deeper Intelligence

Sisense

From data preparation , with attendant data quality assessment, to connecting to datasets and performing the analysis itself, helpful AI elements, invisibly integrated into the platform, make analysis smoother and more intuitive. Call centers already report that AI chatbots receive higher customer ratings than human agents!

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Automating Model Risk Compliance: Model Validation

DataRobot Blog

These methods provided the benefit of being supported by rich literature on the relevant statistical tests to confirm the model’s validity—if a validator wanted to confirm that the input predictors of a regression model were indeed relevant to the response, they need only to construct a hypothesis test to validate the input.

Risk 52
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AI In Analytics: Today and Tomorrow!

Smarten

The value of an AI-focused analytics solution can only be fully realized when a business has ensured data quality and integration of data sources, so it will be important for businesses to choose an analytics solution and service provider that can help them achieve these goals.