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Author: Adnan Masood

MIT Machine Learning for Big Data and Text Processing Class Notes Day 5

Adnan Masood

On the final day (day 5) the agenda for the MIT Machine learning course was as follows: Generative models, mixtures, EM algorithm Semi-supervised and active learning Tagging, information extraction The day started with Dr. Jakkola's discusion on parameter selection, generative learning algorithms,  Learning Generative Models via Discriminative Approaches, and Generative and Discriminative Models. This led to the questions such…

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MIT Machine Learning for Big Data and Text Processing Class Notes Day 4

Adnan Masood

On day 4 of the Machine learning course, following was the agenda: Unsupervised learning, clustering Dimensionality reduction, matrix factorization, and Collaborative filtering, recommender problems The day started with Regina Barzilay (Bio) (Personal Webpage) talk on Determining the number of clusters in a data set and approaches to determine the correct numbers of clusters. The core idea being addressed was difference…

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MIT Machine Learning for Big Data and Text Processing Class Notes Day 3

Adnan Masood

Day 3 of the Machine Learning for Big Data and Text Processing Classification started with Dr. Regina Barzilay (Bio) (Personal Webpage) overview of the the following. Cascades, boosting Neural networks, deep learning Back-propagation Image/text annotation, translation Dr. Barzilay introduced BoosTexter for the class with a demo on twitter feed. BoosTexter is a general purpose machine-learning program based on boosting for building…

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MIT Machine Learning for Big Data and Text Processing Class Notes - Day 2

Adnan Masood

So after having an awesome Day 1 @ MIT, I was in CSAIL library and met Pedro Ortega, NIPS 2015 Program Manager @adaptiveagents. Celebrity sighting! Today on Day 2, Dr. Jaakkola (Bio) (Personal Webpage) professor, Electrical Engineering and Computer Science/Computer Science and Artificial Intelligence Laboratory (CSAIL), went over the following . Non-linear classification and regression, kernels Passive aggressive algorithm Overfitting, regularization, generalization Content…

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MicroServices - Selected Links & Resources.

Adnan Masood

Microservices: An Unexpected Journey (Sam Newman) http://www.slideshare.net/spnewman/qcon-sao-paulo-keynote-microservices-an-unexpected-journey Microservices @ Netflix: A Challenge of Scale http://www.slideshare.net/stonse/microservices-at-netflix Principles of Microservices (ThoughtWorks) http://www.slideshare.net/spnewman/principles-of-microservices-ndc-2014 Developing Enterprise Applications for the Cloud: From Monolith to Microservices (IBM) http://www.slideshare.net/davidcurrie/developing-enterprise-applications-for-the-cloudfrom-monolith-to-microservices Testing & Deploying Microservices (ThoughtWorks) http://www.slideshare.net/spnewman/testing-deploying-microservices-xp-days-ukraine-2014 Growing a Microservices Landscape (With Smart Use Cases) http://www.slideshare.net/aahoogendoorn/20141222-growing-a-microservices-landscape-with-smart-use-cases Think Small to Go Big - Introduction to…

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Deep Learning with Neural Networks

Adnan Masood

Deep learning architectures are built using multiple levels of non-linear aggregators, for instance neural nets with many hidden layers. In this introductory talk Will Stanton discusses the motivations and principles regarding learning algorithms for deep architectures. Bill provides a primer to neural networks, and deep Learning. He explains how Deep Learning gives some of the best-ever solutions to problems…

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