Course Information
Course Overview
A journey into Machine Learning concepts using your very own Artificial Neural Network: Load, Train, Predict, Evaluate
- Cars that drive themselves hundreds of miles with no accidents?
- Algorithms that recognize objects and faces from images with better performance than humans?
All possible thanks to Machine Learning!
In this course you will begin Machine Learning by implementing and using your own Artificial Neuronal Network for beginners.
In this Artificial Neuronal Network course you will:
- understand intuitively and mathematically the fundamentals of ANN
- implement from scratch a multi layer neuronal network in Python
- load and visually explore different datasets
- transform the data
- train you network and use it to make predictions
- measure the accuracy of your predictions
- use machine learning tools and techniques
Jump in directly:
- All sourcecode and notebooks on public GitHub
- Apply Machine Learning: section 4
- Implement the ANN: section 3
- Full ride: section 1, 2, 3, 4
Course Content
- 5 section(s)
- 28 lecture(s)
- Section 1 Introduction
- Section 2 Neuron
- Section 3 Implementation
- Section 4 Applications
- Section 5 Valuable Resources
What You’ll Learn
- Build from scratch your own Artificial Neural Network
- Know the fundamentals of Machine Learning and ANN
- Train your ANN using 3 different datasets with increasing complexity
- Predict the correct output using your trained ANN
- Evaluate the accuracy of your predictions
- Use scikit-learn, numpy and opencv
Reviews
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RRonald Akerman Ortiz Garcia
Buen curso para adquirir las bases de conocimiento en neurona y perceptron
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SSascha Degener
I really liked this course. It's a good starting point for ann!
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AAndre Fritsche
A very nice introduction into neural networks with Python, easy explained. Although you should bring some Python know-how with you.
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HHamed Haddadian
Its just watching some one typing code. there are videos that he is just typing without any sound or explanation.