Insights into the power of machine learning, and the multitude of intelligent applications that can be developed.
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Updated
May 18, 2017
Insights into the power of machine learning, and the multitude of intelligent applications that can be developed.
Repo Contains codes for ML Spec
This repo Contains the codes for the ML Specialization.
Machine Learning Specialization work from UW on Coursera
Esercizi e piccoli Progetti di applicazione all'Intelligenza Artificiale utilizzando GraphLab Create e Python
Esercizi e piccoli Progetti avanzati di applicazione all'Intelligenza Artificiale ed al Machine Learning utilizzando GraphLab Create, Google TensorFlow e Python
Machine learning boiler plate to get you started in minutes (graphlab + sframe + jupyter + docker)
University of Washington MOOC | Practical case-studies from regression and classification to deep learning and recommender systems
Built prediction and retrieval models for document retrieval, image retrieval, house price prediction, song recommendation, and analyzed sentiments using machine learning algorithms in Python
Data Science and ML work in R and Python
Python application, classifies English apps to different categories by their description, using ML algorithms.
This repository contains all the concepts I have tried to work on. Any suggestions or useful advises shall be greatly appreciated
This repo is for ML Specialization through UW on Coursera
Implement the EM algorithm for a Gaussian mixture model and apply it to cluster images
Predicting sentiment from product reviews using graph-lab
Using deep features to build an image classifier using graph-lab
Building an image retrieval system with deep features using graph-lab
Document retrieval from Wikipedia data using graph-lab
A class of clustering methods that seek to build a hierarchy of clusters, in which some clusters contain others
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