AI & Machine Learning

If you’re new to data science, you might be struggling with the coding part. Maybe you sometimes get an error that makes you feel like you might not be able to ever solve it. You struggle with not so much the building of the code but error resolving and debugging because they get stuck with problems they’ve never experienced before.

Deployment is hard. Machine learning models can take on a life of their own.Here’s a list of five practical steps for future-proofing your model against these challenges of model selection and deployment.

Conversational AI is a cost-effective solution to improving every touchpoint between your business and people who need answers or support. Use Conversational AI to improve service to customers, vendors, partners, and any other touchpoint where people contact your business for answers.

This article shows the steps to create an interactive dashboard, using PlotlyDash, a library for Python and R, and enhancing the layout with CSS Bootstrap.

The growth estimated for AI is huge and shows that it will rise by billions in the coming years. AI may be much larger, analysts say that this sector would rise 30 percent annually. AI has tremendous potential because it can go from engineering to tech in any field and can affect everything in between.

Business users of Machine Learning models often ask to “explain” how models make their predictions. Unfortunately, providing such an explanation is not always possible. This is especially true for complex models whose main purpose is to make accurate predictions.

Over the last few years, there has been a clear discrepancy between the data strategies of large and small businesses. Large companies believed a data strategy was crucial to their business models. However, their smaller counterparts have been more likely to procrastinate investing in data-driven business models. This is changing in the wake of the ongoing pandemic.

Data cleaning is not an easy task and most of the time it is time-consuming and tedious, yet this process is too important to be neglected.

The danger of apophenia in analytics and what you can do about it There’s a fine line between telling stories with data and telling lies. Before I tell you how to spot a top-notch data analyst and boost your analytical excellence, let me scare you a little. The psychological trap in data analytics Human brains are pattern-finding powerhouses… but

Over the last century, many connectivist and symbolic implementations of Artificial Intelligence (AI) systems have been implemented in the hope to create Intelligent systems. Although, still nowadays we can’t be sure if using either or both of these two approaches it would ever be possible to create a Strong AI system.

At the core of the new firm is a decision factory – the AI factory that treats decision-making as a science. Analytics systematically convert internal and external data into predictions, insights, and choices, which in turn guide and automate operational workflows.