Keras provides a powerful tool for creating and training neural networks, allowing Python applications to answer complex questions such as predicting website traffic or stock prices. With Keras, machine learning is now fully accessible.
Convolutions for Text Classification with Keras
3.0
Coursera21 learners
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This course is perfect for those who want to learn how to use convolutions in natural language processing tasks such as text classification. With this hands-on, guided introduction to Text Classification using 1D Convolutions with Keras, you will be able to apply word embeddings, use 1D convolutions as feature extractors, and perform binary text classification using deep learning. As a case study, you will work on classifying a large number of Wikipedia comments as being either toxic or not. This course is best suited for those with prior experience in Python programming, deep learning theory, and have used either Tensorflow or Keras to build deep learning models.
Understanding Deepfakes with Keras
2.5
Coursera85 learners
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This course is perfect for those who want to learn how to implement and train DCGAN to generate realistic looking synthesized images. With this 2-hour long project-based course, you will get instant access to a cloud desktop with Python, Jupyter, and Tensorflow pre-installed. You will also need some prior experience with Python programming and a theoretical understanding of Neural Networks, Convolutional Neural Networks, and optimization algorithms like Gradient Descent. This course works best for learners based in the North America region.
Generate Synthetic Images with DCGANs in Keras
3.0
Coursera50 learners
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This course on Coursera's Rhyme platform will teach you how to generate synthetic images with Deep Convolutional GANs (DCGANs) in Keras. You will learn about Generative Adversarial Networks (GANs) and build and train a DCGAN with Keras to generate images of fashionable clothes. You will get instant access to a cloud desktop with Python, Jupyter, and Keras pre-installed, and you can access the cloud desktop 5 times. This course is best suited for learners based in North America, but other regions are being worked on.
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