If you enjoyed this book, you may be interested in these other books by Packt:
Predictive Analytics with TensorFlow
Md. Rezaul Karim
ISBN: 978-1-78839-892-3
- Get a solid and theoretical understanding of linear algebra, statistics, and probability for predictive modeling
- Develop predictive models using classification, regression, and clustering algorithms
- Develop predictive models for NLP
- Learn how to use reinforcement learning for predictive analytics
- Factorization Machines for advanced recommendation systems
- Get a hands-on understanding of deep learning architectures for advanced predictive analytics
- Learn how to use deep Neural Networks for predictive analytics
- See how to use recurrent Neural Networks for predictive analytics
- Convolutional Neural Networks for emotion recognition, image classification, and sentiment analysis
scikit-learn Cookbook - Second Edition
Julian Avila, Trent Hauck, Trent Hauck, These popular $10 titles might interest you, Trent Hauck, These popular $10 titles might interest you, Learning
ISBN: 978-1-78728-638-2
- Build predictive models in minutes by using scikit-learn
- Understand the differences and relationships between Classification and Regression, two types of Supervised Learning.
- Use distance metrics to predict in Clustering, a type of Unsupervised Learning
- Find points with similar characteristics with Nearest Neighbors.
- Use automation and cross-validation to find a best model and focus on it for a data product
- Choose among the best algorithm of many or use them together in an ensemble.
- Create your own estimator with the simple syntax of sklearn
- Explore the feed-forward neural networks available in scikit-learn