Machine Learning

• Important ML Algorithms: Ravit Jain

  Important ML Algorithms

• Difference between logit and probit models
• Correlation can be highly misleading.: Avi Chawla

  Correlation can be highly misleading. . . Many solely rely on the correlation matrix to study the association between variables.

  But unknown to them, the obtained statistic can be heavily driven by outliers.

  This is evident from the image below.

  The addition of just two outliers drastically changed: - the correlation - the regression fit

  Thus, plotting the data is highly important.

  This can save you from drawing wrong conclusions, which you may have drawn otherwise by solely looking at the summary statistics.

  

• Why multi-collinearity is a problem in linear regression?
• What is the difference between test set and validation set?
• Why only three partitions (training, validation, test)
• Cross Validation Vs Train Validation Test
• Classification vs. Prediction: FHarrell.com
• Is accuracy an improper scoring rule in a binary classification setting?
• Why is accuracy not the best measure for assessing classification models?
• Damage Caused by Classification Accuracy and Other Discontinuous Improper Accuracy Scoring Rules: FHarrell.com
• Downsampling vs upsampling on the significance of the predictors in logistic regression
• Ways to remember the definitions of Type I and Type II Errors?
• KMeans: How to understand the drawbacks of K-means
• Intuitive explanation of entropy: 🔥🔥🔥
• What is entropy and information gain?
• What is the difference between Cross-entropy and KL divergence?
• How does a Support Vector Machine (SVM)work?
• Intuitive Way To Understand Principal Component Analysis
• Makingsense of principal component analysis, eigenvectors & eigenvalues
• What are the differences between Factor Analysis and Principal Component Analysis?
• What is the intuition behind SVD?
• Relationship between SVD and PCA. How to use SVD to perform PCA?
• Intuitive explanation of how UMAP works, compared to t-SNE