machine learning for beginners - neural networks
- 4.3
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Brief Introduction
Create you first neural networks in python - a hands on guide for beginnersDescription
What is machine learning / ai ? How to lean machine learning in practice?
machine learning / ai (artificial intelligence) and neural networks (often referred to as deep learning) are one of the hottest topics in this century - for good reasons.
There are a lot of interested people out there but many do not know where to start. The difficult question basically is how to start actually learning it?
Especially beginners might get discouraged because of statistics and math which is an integral part of machine learning. Also matrix operations in tensorflow are not considered easy peasy. None the less you do not need to be a math expert to apply machine learning. This is my third course to show you why.
Instead of telling you all the statistics and math behind the neural network and deep learning i prefer to give you a much more hands on approach. At the end of the day there's only one thing that really counts - THE RESULT. I believe in a practical approach. That's why the course is developed to encourage you to follow along and write the code yourself. At the end you can see your result.
By joining this course you can leverage the knowledge you acquired from my first two courses (Machine Learning for Beginners and machine learning for beginners - deep dive) and get the chance to dive into theworld of neural networks. Again this course is not for students who like to learn theory. Those should rather turn to a university professor or wikipedia.
But if you want to actually practise machine learning and neural networks with python and tensorflow and learn how to write and improve your own algorithms then this beginner's course is the right way to continue your learning journey!
I wish you all the best, enjoy the course, get your hands dirty and start coding! Let's master neural networks from scratch
See you in the first lecture
Addon Updates:
If you want to dive deeper into Neural Nets and learn to understand and program more than check out my additional courses which cover additional content which will give you additional knowledge.
- A beginners guide for building neural networks in tensorflow
- neural networks transfer learning and sentiment prediction
- How neural networks work - a glimpse into math for beginners
- A crash course in neural networks for beginners
- A crash course in neural networks for beginners - deep dive
- machine learning and neural networks mini case studies
- neural networks for beginners from scatch
- machine learning with text for beginners
You can easily find them by checking out my instructor profile.
Requirements
- Requirements
- !Please note I reupload all files in a larger size and appended them at the end
- Install Python and the relevant modules (numpy, keras, tensorflow/theano e.g. via Pip)
- Being familiar with basic Python syntax
- This is a hands-on approach and not a university lecture with lots of theory
- I believe in praxis - so I want you to code with me
- Note that I use tensorflow 0.12.1 and keras 1.2.2 versions here. Other versions could cause problems since modules and names where changed! To follow here install my versions
- Theoretical background is certainly helpful and can easily found on wikipedia or other sources
Dan We
4.3 Raiting
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