Deep Learning in collaboration with AWS and Facebook AI
Skills Covered: Deep Learning, Jupyter Notebooks, CNNs, GANs, Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Generative Adversarial Networks
ABOUT THIS NANODEGREE
Deep Learning, also called a deep neural network or deep neural learning is one of the fast-growing artificial intelligence functions. It drives advances in artificial intelligence that are changing our world. Become a world-class expert in deep learning.
Learn how to build and apply neural networks in image recognition, recurrent networks for sequence generation, and how to deploy models accessible from a website. Apply style transfer to images, and learn how to use development tools such as Jupyter notebooks and Anaconda. Build your first network with NumPy and Python. Build multi-layer neural networks using modern deep learning framework PyTorch and analyze real data. Build convolutional networks, use them to classify images (faces, melanomas, etc.) based on patterns and objects. Use networks to learn data image denoising and data compression. Learn how to build your own recurrent networks and memory networks with PyTorch. Discover how to use recurrent networks to generate new text from TV scripts and perform sentiment analysis.
Meet Ian Goodfellow, the inventor of GANs, and Jun-Yan Zhu, the creator of CycleGANs. They will teach you how to generate realistic images by implementing a Deep Convolutional GAN (generative adversarial network). Build and deploy your own PyTorch sentiment analysis model and create a gateway for accessing it from a website.
The share of jobs requiring AI skills has grown 4.5x since 2013
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