AI & ML
Deep Learning with Python and PyTorch
This training program is all about how to develop Deep Learning models using Pytorch.
What is Deep Learning with Python and PyTorch Training about?
Learn how to build and train deep neural networks—learning how to apply methods such as dropout, initialization, different types of optimizers and batch normalization. We will then focus on Convolutional Neural Networks, training your model on a GPU and Transfer Learning (pre-trained models). You will finally learn about dimensionality reduction and autoencoders. Including principal component analysis, data whitening, shallow autoencoders, deep autoencoders, transfer learning with autoencoders, and autoencoder applications.
What are the objectives of Deep Learning with Python and PyTorch Training ?
By the end of this training, you will be able to:
- Apply knowledge of Deep Neural Networks and related machine learning methods
- Build and Train Deep Neural Networks using PyTorch
- Build Deep learning pipelines
Who should take this Deep Learning with Python and PyTorch Training?
- Learners who want to advance their knowledge on Machine Learning
What are the prerequisites for Deep Learning with Python and PyTorch Training?
- Python & Jupyter notebooks
- Machine Learning concepts
- Deep Learning concepts
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