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!
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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