Data Preprocessing

Improving Sequential Recommender Systems with AutoMLP: A Solution to Long/Short-Term Interest Identification

In recent years, sequential recommender systems have emerged as a popular approach for providing personalized recommendations to users. These systems take into account the order in which items are consumed by users, enabling them to identify long-term and short-term interests of users and predict their future preferences accurately. However, while sequential recommender systems have proven …

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FP-Growth vs. Apriori: A Comprehensive Comparison of Frequent Pattern Mining Algorithms

Introduction Frequent Pattern Mining, also known as Association Rule Mining, is a powerful analytical process that helps in discovering frequent patterns, associations, or causal structures from various databases such as relational and transactional databases. It plays a significant role in Market Basket Analysis, a data analysis technique used by retailers to identify patterns in customer …

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Using Multivariate Time Series Forecasting with Transformers in Finance

In today’s fast-paced financial world, businesses require accurate and timely financial forecasting to make informed decisions. Multivariate time series forecasting has become a popular technique in finance to predict future values of multiple variables simultaneously. It is a statistical method that models the behavior of several interdependent variables over time, considering the historical data of …

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Making Machine Learning Predictions at Scale: Building High-Performance Pipelines

Machine learning (ML) has become an integral part of many industries and businesses, enabling the development of intelligent systems that can make predictions and decisions based on data. However, as the volume and complexity of data continues to grow, so too does the challenge of making predictions at scale. This requires building high-performance pipelines that …

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