Machine Learning Useful LinksMachine Learning Useful Links

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In this guide I am sharing some useful links related to Machine Learning and Algorithms. These tutorial will help anyone preparing for ML algorithm or learning about ML in general. Machine Learning:https://www.edureka.co/blog/interview-questions/machine-learning-interview-questions/ https://www.springboard.com/blog/machine-learning-interview-questions/ https://www.analyticsvidhya.com/blog/2016/09/40-interview-questions-asked-at-startups-in-machine-learning-data-science/ Confusion Matrix:https://towardsdatascience.com/beyond-accuracy-precision-and-recall-3da06bea9f6c https://www.kdnuggets.com/2020/01/guide-precision-recall-confusion-matrix.html#: Logistic Regression: https://www.datacamp.com/community/tutorials/understanding-logistic-regression-python Decision Tree: https://www.edureka.co/blog/decision-trees/ https://www.geeksforgeeks.org/decision-tree-introduction-example/ Random Forest: https://towardsdatascience.com/an-implementation-and-explanation-of-the-random-forest-in-python-77bf308a9b76 https://www.analyticsvidhya.com/blog/2015/06/tuning-random-forest-model/#:~:text=n_estimators%20%3A,but%20makes%20your%20code%20slower. Naive Bayes: