This course on Machine Learning will explain how to build systems that learn and adapt using real-world applications. Some of the topics to be covered include machine learning, python data analysis, deep learning frameworks, natural language processing models and recurrent models. The course will be project-oriented, with emphasis placed on writing software implementations of learning algorithms applied to real-world problems, in particular, image analysis, image captioning, natural language processing, sentiment detection, among others.

https://github.com/albahnsen/PracticalMachineLearningClass

This course on Deep Learning will explain how to build systems that learn and adapt using real-world applications. Some of the topics to be covered include deep learning frameworks, convolutional neural networks, generative models nadrecurrent models. The course will be project-oriented, with emphasis placed on writing software implementations of learning algorithms applied to real-world problems, in particular, image analysis, image captioning, natural language pocessing, sentiment detection, among others.

https://github.com/albahnsen/AppliedDeepLearningClass

Short course teaching the basics of Machine Learning for Risk Management (Mostly towards retail banking)

Version 2 – 8 Hours – February 2018

Version 1 – 16 Hours – October 2016

Tutorial given at Pycon 2017 and Pycon.co 2018.

Course on machine learning. Mostly focused towards the application of machine learning algorithms in several real-world applications.

https://github.com/albahnsen/PracticalMachineLearningClass/tree/Class2016