Machine learning and AI-based techniques use complex algorithms that can contribute to solving complex cost and delivery problems faced by an increasing number of enterprises today. Deploying the right ML model, enterprises can draw significant insights on how to improve and optimize their supply chain performance. By anticipating anomalies in logistics costs in real-time, AI in machine learning can help companies bring down revenue losses tremendously
Roaring magnanimously, artificial intelligence has emerged as one of the most widely used technologies in every industry today. Looking at the graph below, it is clear that artificial intelligence has established a strong foothold in supply chain management as well. In fact, AI in the supply chain comes at the third...
Data-Driven Transformation Affair in Retail Retail is one of the strongest and fastest-growing industries worldwide. 2019 onwards it will further pick up the pace and witness a glorious data-driven transformation. If you take a look at the statistics, the global retail industry is expected to register a CAGR of 5.3%...
Traditional Forecasting Methods As seen in Part 1, Forecasting is an important part of the demand planning strategy. Human beings have been cognizant of the importance of forecasting since time immemorial. We have forecasted weather patterns to understand mother nature to become an agrarian community from hunters an...
Container Orchestration - Kubernetes As we know how popular the Containers have become in today’s IT world. Most of the large organizations have moved out of their traditional approach of using virtual machines and started adapting Containers for deployment. Kubernetes (“koo-burr-NET-eez”) is the conventional pron...
We will discuss different data normalisation methods such as value mapping normalisation, discretization normalisation, equal width discretization , egual frequency discretization and aggregation normalisation
Data Transformation | Normalisation techniques In the part 1 of the series we looked at the various methods of normalising the data including min-max and box-cox transformations. In this part we look at the following Value Mapping Discretization Equal Width Discretization Equal Frequency Discretization Aggrega...
The process of normalisation entails converting numerical values into a new range using a mathematical function. Two common normalisation methods are min-max normalisation and z score normalisation
Data Transformation | Normalisation Techniques Almost always when we get raw data in any project, it is unfit for direct consumption for analysis or modelling . It is a especially a concern when the data volume is huge for example in a big data analytics project . In this blog post I cover a few of the most commo...
