What do you think?
Rate this book
Advanced Machine Learning with Python
Solve challenging data science problems by mastering cutting-edge machine learning techniques in Python.
- GenresNonfiction
254 pages, Unknown Binding
Published January 1, 2016
1 person is currently reading
37 people want to read
Ratings & Reviews
Friends & Following
Create a free account to discover what your friends think of this book!
Community Reviews
Displaying 1 - 2 of 2 reviews
February 15, 2018
Nice overview of the concepts
December 20, 2016
This book illustrates less common machine learning algorithms mainly using the Python Theano library.
It covers many approaches including self-organising maps, PCA, deep learning (RNN, CNN, Autoencoders) as well as semi-supervised learning such as Contrastive Pessimistic Likelihood estimation (CPLE). It uses well-known datasets used in machine learning contests such as MNIST or CIFAR-10.
For a book about Deep learning, I like it better than Deep Learning: A Practitioner's Approach because it covers more ground but is not restricted to Deep Learning ideas. Yet, I found theoretical models of CNN, RNN, and the likes are only too briefly discussed.
It covers many approaches including self-organising maps, PCA, deep learning (RNN, CNN, Autoencoders) as well as semi-supervised learning such as Contrastive Pessimistic Likelihood estimation (CPLE). It uses well-known datasets used in machine learning contests such as MNIST or CIFAR-10.
For a book about Deep learning, I like it better than Deep Learning: A Practitioner's Approach because it covers more ground but is not restricted to Deep Learning ideas. Yet, I found theoretical models of CNN, RNN, and the likes are only too briefly discussed.
Displaying 1 - 2 of 2 reviews