„Deep Learning Crash Course“
video guide: Oliver Zeigermann
Manning Early Access Program (MEAP), Manning Publications
published November 2018
liveVideo – Deep Learning Crash Course at manning.com
With an emphasis on simplicity, Deep Learning Crash Course teaches you to build machine learning models, the part of a system that makes classifications and predictions. You’ll also learn how to apply algorithms that train the model to improve based on the data it encounters. Your video guide Oliver Zeigermann launches your learning with a spotlight on how deep learning is different from other programming and data analysis techniques. You’ll work through a complete project and learn to use the most popular Python-based deep learning tools, including scikit-learn, Keras, and TensorFlow
All the tools are free and open source. The incredible machine learning library Keras has a minimalistic, instantly-comfortable API that handles most of the math, so you’ll get the maximum return on your time. As you work your way through this practical video course, you’ll gain skills like training a neural network, creating and executing TensorFlow code, encoding your data, and making your model more general. By the end, you’ll know how to evaluate your results, debug and improve your model, and deploy it for production.
- The basics of neural networks
- Machine learning techniques using Scikit-learn, TensorFlow, and Keras
- How to train a machine learning model and evaluate the results
- Debugging and improving your model
- Deployment in a production environment
Prerequisites: You need beginner to intermediate Python programming skills and some experience working with organized data files, such as databases or spreadsheets.
follow us on Twitter – @embarced