Topic: python
NLP - Lexical Processing
Preface Word Frequencies and Stop Words Tokenisation Bag-of-Words Representation Stemming and Lemmatization Stemming Lemmatization TF-IDF…
NLP - Regular Expressions
Preface Areas of Application Understanding Text Text Encoding Encoding Standard Regular Expressions Quantifiers White Space Parentheses Pipe…
Gaussian Mixture Models
Purpose Limitations of K-Means Advantages of GMMs over K-Means Limitations of Fitting the Data using a Single Gaussian 1D Gaussian vs…
Support Vector Machines
Support Vector Machines Maximal Marginal Classifier Soft Margin Classifier Summary Questions Kernels Boundary Transformation Feature…
Principal Component Analysis
Principal Component Analysis Problem with having a lot of features Applications of PCA Dimensionality Reduction PCA Definition PCA - Change…
Model Selection - Practical Considerations
Business Case Identifying the consumers of an e-commerce website Based on Gender Based on Age Benefits of Identifying the right consumer…
Unsupervised Learning
Types of Learning Unsupervised Learning Practical applications of Clustering Clustering vs Segmentation Segmentation Stability Inter and…
Boosting
Purpose Bagging vs Boosting Bagging Boosting Question Weak Learners Question AdaBoost Steps Question Amount of Say Change of Weight…
Ensembles and Random Forest
Purpose Ensembles Idea Diversity Ways to achieve diversity Acceptability Why ensembles work Example Coin Toss Explanation Voting Stacking…
Decision Trees
Purpose About Decision Trees Building Decision Trees Top Down Greedy Question Hyperparmaeters Hyperparameter Tuning Difference between…
Logistic Regression in the Industry
Purpose of Logistic Regression Difference between Linear Regression and Logistic Regression Why is Logistic Regression so common Confusion…
Advance Regression - Ridge, Lasso, Gradient Descent
Constrained Minimization Ridge and Lasso Regression Signature of overfitting in Polynomial Regression Ridge Lasso Unconstrained Minimization…
Model Selection
Purpose Choice of Model Selection Practical Issues Domain Knowledge Class of Models Occams Razor Which model should be picked Example…
Linear Regression in the Industry
Purpose Understanding the use of Linear Regression in the Industry / Real World Uses Forecasting Prediction Linear Regression can show…
Receiver Operating Characteristic (ROC) Curve
Purpose Understanding ROC Curve ROC ROC stands for Receiver Operating Characteristic curve. This name has emerged from the domain of…
Maximum Likelihood Estimation
Purpose Cost Function Closed Form Iterative Method Random Variables Maximum Likelihood Cost Function What is MLE Finding Parameters of…
Important Topics from Stats and ML
Random Variable which maps the output of a random experiment to a numerical value Radom Experiment Example: tossing a coin Expected Value…
Multiple Linear Regression
Purpose Effect of adding more variables on $R^2$ Formulation of Multiple Linear Regression Interpretation of the coefficients Some aspects…
Pandas Basics
Table of Contents Frequency Table using pd.crosstab References What is Pandas Pandas is a library specifically aimed at simplifying the…
Naive Bayes Classification
Purpose Notes on Naive Bayes Classifier About Naive Bayes is a probabilistic classifier which returns the probability of a test point…