Dipti

Over the last couple of articles, We learned different classification and regression algorithms. Now in this article, We are going to learn entirely another type of algorithm. Which falls into the unsupervised learning algorithms . If you were not aware of unsupervised learning algorithms, all the machine learning algorithms mainly classified into two main categories. Supervised learning algorithms Unsupervised learning algorithms All the classification and regression algorithms belong to supervised learning algorithms. The other set of algorithms which fall under unsupervised learning algorithms are clustering algorithms. In fact, the foremost algorithms to study in unsupervised learning algorithms is clustering analysis algorithms. Today we are going to learn an algorithm to perform the cluster analysis. We have a decent number of algorithms to perform cluster analysis; In this article, we will be learning how to perform the clustering with the Hierarchical clustering algorithm. Loo...

  As artificial intelligence continues to evolve, businesses are realizing that generalized tools aren’t enough. Each industry has distinct data structures, compliance needs, and operational challenges. That’s why more organizations are partnering with a specialized AI consulting company to build industry-specific solutions. From retail and healthcare to manufacturing and finance, the need for domain-aware AI is driving the next wave of innovation. These solutions aren’t just intelligent — they’re relevant, precise, and built to scale. Why Industry-Specific AI Matters What works for an e-commerce retailer doesn’t necessarily apply to a logistics company or a healthcare provider. For example: Retailers need dynamic pricing and personalized recommendations. Healthcare institutions focus on patient risk scoring and diagnostics. Manufacturers require predictive maintenance and supply chain optimization. Instead of forcing a universal solution into diverse environments, businesses...

Statistics in Tableau Data in the right hands can be extremely powerful and can be a key element in decision making. American statistician, W. Edwards Deming quoted that, “In God we trust. Everyone else, bring data”. We can employ statistical measures to analyze data and make informed decisions. Tableau enables us to calculate multiple types of statistical measures like residuals, correlation, regression, covariance, trend lines and many more. Today let’s discuss how people misunderstand causation and correlation using Tableau. Correlation and Causation Correlation is a statistical measure that describes the magnitude and direction of a relationship between two or more variables. Causation shows that one event is a result of the occurrence of another event, which demonstrates a  causal relationship between the two events. This is also known as cause and effect. Types of correlation: 1 → Positive correlation. -1 → Negative Correlation. 0 → No correlation. Why are correl...