Intro to Machine Learning with Python

By Bernd Klein. Last modified: 17 Feb 2022.

Machine Learning

Machine learning is is the kind of programming which gives computers the capability to automatically learn from data without being explicitly programmed. This means in other words that these programs change their behaviour by learning from data.

We will cover various aspects of machine learning in this tutorial. Of course, everything will be related to Python. So it is Machine Learning by using Python. It might well be that you came to this website when looking for an answer to the question: What is the best programming language for machine learning? Python is clearly one of the top players!

machine learning: robot jugglers

We will cover in this tutorial on Machine Learning and Python the following topics amongst others:

k-nearest Neighbor Classifier
Neural networks
- Neural Networks from Scratch in Python
- Neural Network in Python using Numypy
- Dropout Neural Networks
- Neural Networks with Scikit
- Machine Learning with Scikit and Python
Naive Bayes Classifier
Introduction into Text Classification using Naive Bayes and Python

Machine learning can be roughly separated into three categories:

Supervised learning: The machine learning program is both given the input data and the corresponding labelling. This means that the learn data has to be labelled by a human being beforehand.
Unsupervised learning: No labels are provided to the learning algorithm. The algorithm has to figure out the a clustering of the input data.
Reinforcement learning: A computer program dynamically interacts with its environment. This means that the program receives positive and/or negative feedback to improve it performance.

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In this chapter

Page	Description
1. Machine Learning with Python	Introduction in Machine Learning and Python
2. Machine Learning Terminology	Machine Learning related Terminology used in this Tutorial
3. Evaluation Metrics	Python Machine Learning: Difference between Accuracy and precision, recall, F1-Score
4. Data Representation and Visualization of Data	Data representation and visualization in Machine Learning with Python
5. Available Data Sets in Sklearn	Overview and presentation of the available datasets in sklearn
6. Artificial Datasets with Scikit-Learn	Creating Synthetical datasets for Machine Learning usage with and without Scikit-Learn (sklearn)
7. Train and Test Sets by Splitting Learn and Test Data	Data Sets in Machine Learning, splitting them in learn and test sets with Python
8. k-Nearest Neighbor Classifier in Python	Introduction into k-nearest neighbor classifiers with Python
9. k-Nearest-Neighbor Classifier with sklearn	k-nearest neighbor classifiers with Python and sklearn
10. Neural Networks Introduction	Tutorial on Neural Networks with Python
11. Separating Classes with Dividing Lines	Showing the connection between dividing lines (decision boundaries) and neural networks with a single perceptron using Python
12. A Simple Neural Network from Scratch in Python	Examining simple neural networks with one perceptron. Pointing out the limits by using Python programs.
13. Perceptron class in sklearn