Regression and Time Series Analysis
Linear regression, nonlinear regression, auto-regressive models, time series analysis, regularisation and more.
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two days Course
What you will learn
You will learn the skills you need to develop and evaluate regression models that allow you to make quantitative predictions.
- Multivariate linear regression
- Ridge and LASSO regularisation
- Logistic regression and generalised linear models
- Time series analysis: AR, MA, ARMA and ARIMA models
Languages and libraries
- Python 3
- Numpy and Pandas for data manipulation
- scikit-learn and statsmodel for linear and time series models
- matplotlib for visualisation
Learn state-of-the art machine learning techniques at our Machine Learning Techniques using Python bootcamp.
Acquire specialised Natural Language Processing skills at our Text Mining and Natural Language Processing with Python bootcamp.
Prerequisites: Good knowledge of python, basic understanding of machine learning practice (as taught in Introduction to Data Science)
- Multivariate regression using SKLearn
- Outliers, leverage, analysis of diagnostics
- Data transformations
Regularisation: Ridge and LASSO
- The Ridge regression
- The LASSO regression
- Applications and comparisons
Generalised linear models
- The Logistic regression
- Use of regularisation
- Applications in industry
- Drinks with fellow participants and lecturers
Time series analysis
Handling time series
- Manipulating time series with Pandas
- Handling trends and seasonalities in time series: understanding lagging
- Autocorrelation function and moving average (MA)
Time series models
- Building an autoregression (AR)
- Adding structure in a time series model: towards ARMA and ARIMA models
- Modeling real-world time series: how to avoid pitfalls
Continuous learning project
Our continuous learning project comprises a real-world problem and data set to complete in your own time, and practice using the course material and techniques covered during the bootcamp. The package includes model notebook answers, with a detailed explanation of the solution and problem-solving process.Price: £100 extra