Computer vision is a key aspect of artificial intelligence that is critical to many applications, from robots movements to self-driving cars and from medical imaging to products recognition in manufacturing plants. This MIT course presents the issues of computer vision…
Conceptual and mathematical summary for machine learning
Machine learning makes use of multiple mathematical formulas and relations to implement the different tasks it can handle. Gathered in the following “cheat sheets” by Afshine and Shervine Amidi, the concepts for supervised and unsupervised learning, deep learning together with machine…
Guide to real Machine Learning applications
This series of articles dives deeper into the actual applications of Machine Learning that are currently in use in many current technological processes and devices. Through these posts entitled “Machine Learning is Fun!”, Adam Geitgey guides us step by step…
Catalogue of neural networks architectures
Neural networks come in a wide range of shapes and functions, with diverse architectures and parameters for input, hidden and output nodes as well as convolutive or recurrent nodes. Regrouped in a convenient summary by Fjodor Van Veen, the most…
Programming a simple classifier with TensorFlow
TensorFlow is an open-source machine learning framework developed by Google. It relies upon Tensors (multi-dimensional arrays) which empower a wide range of API to develop machine learning applications, primarily deep neural networks. TensorFlow is commonly used in machine learning practice,…