Introduction to Data Science 1MS041
You can download the Lecture notes here.
Precision Recall survey here
Introductory Jupyter .ipynb Notebooks
These notebooks contain the basic theory of how to work with python and BASH, that will be needed in this course.
A01. A01-BASH_Unix_Shell
Individual Jupyter .ipynb lecture Notebooks
These notebooks are numbered according to which lecture they coincide with and will be updated after the lectures. Before the lecture they can be considered preliminary.
- 01-Probability
- 02-Random_Variables
- 02-Random_Variables_examples
- 03-Random_Variables
- 04-Concentration_and_Limits
- 05-Limits
- 05-Risk
- 06-Fundamentals_of_estimation
- 07-Estimation_Likelihood
- 07-Optimization
- 07-StandardError
- 08-GeneratingRandomVariables
- 08-PRNG
- 09-Markov_chains
- 10-Pattern_Recognition
- 11-Training_Testing_Metrics
- 12-Regression
- 13-High_Dimension
- 14-Dimensionality_Reduction
- 15-Extra_Topics
Problem Solving Sessions
These notebooks are numbered according to which problem solving session they coincide with.
Starting package
- Download the Starting package
- Unzip this into a folder that you will use as the base folder
- Whenever you download the next lectures as
ipynbfiles, you put them in the same place as*.ipynb, this way all pathways will be the same for all of us.