Mastering Machine Learning Algorithms Second Edition

Mastering Machine Learning Algorithms Second Edition

Machine learning is a subset of artificial intelligence that aims to make modern-day computer systems more intelligent. The real power of machine learning lies in its algorithms, which make even the most difficult things capable of being handled by machines. Mastering Machine Learning Algorithms, Second Edition helps you harness the…

Machine Learning Algorithms – Second Edition

The second edition (fully revised, extended, and updated) of Machine Learning Algorithms has been published today and will be soon available through all channels. From the back cover: Machine learning has gained tremendous popularity for its powerful and fast predictions through large datasets. However, the true forces behind its powerful…

Mastering Machine Learning Algorithms

Today I’ve published my latest book “Mastering Machine Learning Algorithms” (in a few days it will be available on all channels). From the back cover: Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides…

Hetero-Associative Memories for Non Experts: How “Stories” are memorized with Image-associations

Think about walking along a beach. The radio of a small kiosk-bar is turned-on and a local DJ announces an 80’s song. Immediately, the image of a car comes to your mind. It’s your first car, a second-hand blue spider. While listening to the same song, you drove your girlfriend…

An annotated path to start with Machine Learning

“Do not worry about your difficulties in Mathematics. I can assure you mine are still greater.” (A. Einstein)   Machine Learning is becoming more and more widespread and, day after day, new computer scientists and engineers begin their long jump into this wonderful world. Unfortunately, the number of theories, algorithms, applications,…

Twitter Sentiment Analysis with Gensim Word2Vec and Keras Convolutional Networks

Fork Word2Vec (https://code.google.com/archive/p/word2vec/) offers a very interesting alternative to classical NLP based on term-frequency matrices. In particular, as each word is embedded into a high-dimensional vector, it’s possible to consider a sentence like a sequence of points that determine an implicit geometry. For this reason, the idea of considering 1D…

SVD Recommendations using Tensorflow

Recommendation system based on the user-item matrix factorization have become more and more important thanks to powerful and distributable algorithms like ALS, but sometimes the number of users and/or items is not so huge and the computation can be done using directly a SVD (Singular Value Decomposition) algorithm. In this…

Lossy image autoencoders with convolution and deconvolution networks in Tensorflow

Fork Autoencoders are a very interesting deep learning application because they allow a consistent dimensionality reduction of an entire dataset with a controllable loss level. The Jupyter notebook for this small project is available on the Github repository: https://github.com/giuseppebonaccorso/lossy_image_autoencoder. The structure of a generic autoencoder is represented in the following figure:…