Join Adam Geitgey for an in-depth discussion in this video What you should know, part of Building Deep Learning Applications with Keras 2.0.
- [Instructor] Before starting this course, it will be helpful to have some programming experience. The examples are written in Python 3, so it's also helpful if you have some familiarity with Python syntax. Regardless, I'll explain things in the way that will be accessible even if you don't have a lot of experience in Python. Also, it will be helpful if you have some basic experience with machine learning. If you're brand new to machine learning, you can check out some of the machine learning courses in the library.
Author
Released
8/1/2017- What's Keras?
- Using Keras vs. TensorFlow
- Training a deep learning model
- Using a pre-trained deep learning model
- Monitoring a Keras model with TensorBoard
- Using a trained Keras model in Google Cloud
Skill Level Intermediate
Duration
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Python: Data Analysis
with Michele Vallisneri2h 16m Intermediate
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Introduction
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Welcome46s
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1. Keras Overview
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What is Keras?1m 59s
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2. Setting Up Keras
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3. Creating a Neural Network in Keras
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Keras Sequential API4m 4s
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Pre-processing training data6m 17s
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4. Training Models
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Making predictions2m 36s
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5. Pre-Trained Models in Keras
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Pre-trained models2m 35s
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6. Monitoring a Keras model with TensorBoard
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Visualize training progress4m 51s
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7. Using a Trained Keras Model in Google Cloud
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Conclusion
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Next steps9s
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Video: What you should know