Explores challenges in data assumptions, biases, and more in research, including incomplete write-ups and frustrations of newcomers.
Covers the challenges and opportunities of data mining, practical questions, algorithm components, and applications like shopping basket analysis.
Explores Association Rule Mining, emphasizing Frequent Itemsets and Alternative Measures of Interest, including the FP-Growth algorithm and performance comparison.
Covers association rules mining, focusing on Apriori and FP-growth algorithms to find frequent itemsets and extract rules efficiently.
