Deep Learning, Neural Networks & AI: The Complete Course
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Deep Learning describes an approach to machine learning that deals with neural networks. Neural networks, in turn, refer to a model for information processing that has been inspired by biological processes in the human brain. In application, predictions and decisions can be calculated with it.
At the beginning of the course, it is explained how neural networks work at all. Then, using various examples, numerous areas of application of deep learning are shown, including:
- How objects are recognized in images in order to then be able to check whether and where certain objects are located in images
- How texts in specific literary styles are generated with the TensorFlow framework
- How future prices are predicted based on Bitcoin and stock prices
- How high scores are achieved in a game ("Flappy Bird")
Through clear explanations, the course offers easy comprehensibility even of the somewhat more demanding methods. Moreover, numerous other practical examples and exercises guide participants to be able to apply their new knowledge to their own projects and problems. Upon completion of the course, participants master practice-relevant tools such as Jupyter, Keras and Tensorflow 2.
At least basic programming knowledge is expected from participants in order to be able to quickly dive into the world of deep learning with this course.