Machine-Learning-Tokyo/DL-workshop-series
Jupyter notebook-based workshop series teaching deep learning with Keras implementations of convolutional neural network architectures.
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This is a Machine Learning Tokyo workshop series providing hands-on educational material for deep learning. The curriculum covers convolution operations and implementations of major CNN architectures including AlexNet, VGG, Inception, MobileNet, ResNet, DenseNet, YOLO, and others using Keras. The material includes Jupyter notebooks for interactive learning along with accompanying YouTube video lectures explaining the implementations and concepts.
Frequently asked
- What is Machine-Learning-Tokyo/DL-workshop-series?
- Jupyter notebook-based workshop series teaching deep learning with Keras implementations of convolutional neural network architectures.
- Is DL-workshop-series open source?
- Yes — Machine-Learning-Tokyo/DL-workshop-series is open source, released under the Apache-2.0 license.
- What language is DL-workshop-series written in?
- Machine-Learning-Tokyo/DL-workshop-series is primarily written in Jupyter Notebook.
- How popular is DL-workshop-series?
- Machine-Learning-Tokyo/DL-workshop-series has 935 stars on GitHub.
- Where can I find DL-workshop-series?
- Machine-Learning-Tokyo/DL-workshop-series is on GitHub at https://github.com/Machine-Learning-Tokyo/DL-workshop-series.