Bias and Variance in Machine Learning – A Fantastic Guide for Beginners!
Overview Learn to interpret Bias and Variance in a given model. What is the difference between Bias and Variance? How to achieve Bias and …
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IBM Open Sources Comprehensive Python Toolkit for Detecting & Fighting Bias (30 Metrics, 9 Algorithms)
Overview IBM has open sourced a toolkit to deal with bias in datasets and algorithms The toolkit contains 30 fairness metrics and 9 state-of-the-art …
Tree Based Algorithms: A Complete Tutorial from Scratch (in R & Python)
Overview Explanation of tree based algorithms from scratch in R and python Learn machine learning concepts like decision trees, random forest, boosting, bagging, ensemble …
Festive season special: Building models on seasonal data
Has your model ever failed on out of time validation because of seasonality? If yes, then you need to know that one of the …
Common data preparation mistakes and how to avoid them?
A few days back, one of my friend was building a model to predict propensity of conversion of leads procured through an Online Sales …
Common mistakes analysts make during analysis and how to avoid them?
Quite often I come across situations where people end up making wrong inferences based on half baked analysis. Or when people force fit data …
