Basic Statistics with Scipy:
- Discrete Statistical Distributions: Binomial Distribution, Poisson Distribution and Geometric Distribution
- Continuous Statistical Distributions: Chi-squared Distribution, Exponential Distribution and Normal Distribution
Classification and Regression:
- Ordinary Least Squares
- Ridge Regression
- Logistic Regression
- Support Vector Machines
- Nearest Neighbours
- Decision Trees
Clustering:
- K-Means
- Spectral Clustering
Dimensionality Reduction:
- Principal Component Analysis
- Latent Dirichlet Allocation (LDA)
- Model selection and evaluation:
- Cross-validation
- Tuning hyper-parameters of an estimator
- Quantify quality of predictions
Pre-processing:
- Standardisation and scaling
- Normalisation
- Encoding categorical features
Natural Language Processing:
- Extract basic features like number of words and characters etc.
- Text pre-processing like punctuation removal, tokenisation, lemmatisation
- Text processing like n-gram, bag of words and name entity recognition