Data Analytics and Machine Learning with Python

Overview

What you will learn

In the Data Analytics and Machine Learning with Python course offered by City, University of London , you will learn:

• Jupyter notebook: a quick tour of the data engineers' IDE of choice.

• Introduction to numpy: N-dimensional arrays, broadcasting functions, linear algebra abstractions and random number generators.

• Exploratory data analysis with pandas: manipulating data: loading, storing, cleaning, transforming, merging, reshaping.

• Visualising and plotting with matplotlib: generate plots, histograms, power spectra, bar charts, errorcharts, scatterplots. Visualize and understand different types of data.

• Introduction to scipy with statistics, is mainly focused at providing a quick introduction to the scipy.stats package. We will be looking at distributions, fitting distributions and random numbers.

• Introduction to machine learning concepts with scikit-learn, training and evaluating learning algorithms. We will be looking at: decision trees, perceptrons, support vector machines, and neural networks.

• Scikit-learn delving deeper: using data validation and cross-validation. Also some other methods to improve the accuracy of your learning algorithms