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DC Homework 2
DC Homework 2
DC Homework 2
Kunal Lad
Propuesta de Proyecto de Electiva III
Propuesta de Proyecto de Electiva III
Minería de datos con Weka para la predicción del precio de automóviles de segunda mano
Mariana Paucar
Economía de la felicidad
Economía de la felicidad
En el siguiente ensayo, usted podrá encontrar encuestas que le brindaran información disponible en la pagina web del DANE, que le mostraran los diferentes estratos socioeconómicos en la ciudad de Medellín. El propósito de este ensayo es mostrar una relación entre los ingresos de los individuos y su felicidad. Dado a que la mayoría de la población de Medellín consta con bajos recursos y sufren necesidades por la falta de ciertas modalidades indispensables para sobrevivir, ellos son felices y están plenos con su estilo de vida.
Maicol Rojas
About Myself (LaTeX Exercise)
About Myself (LaTeX Exercise)
A simple document created with LaTeX.
Marck Ruther Sta. Ines
TRATAMIENTO DE AGUAS NEGRAS Y RESIDUALES Y SU IMPORTANCIA
TRATAMIENTO DE AGUAS NEGRAS Y RESIDUALES Y SU IMPORTANCIA
tratamientos de aguas tanto negras como residuales y su importancia
Santiago Rivera
Where are our Providers?: Image Clustering based on Locations of Brazilian Government Suppliers
Where are our Providers?: Image Clustering based on Locations of Brazilian Government Suppliers
The Observatory of Public Spending (or ODP, in Portuguese) is a special unit of Brazil's Ministry of Transparency, Monitoring and Office of the Comptroller-General (or CGU, in Portuguese) responsible for monitoring public spending and gathering managerial and audit information to support the work of CGU internal auditors. One of the most important themes monitored by this unit is Public Procurements and Government Suppliers which have won these procurement processes. Image analysis of many of these suppliers headquarters revealed suspicious landscapes, such as rural areas, isolated places or slums. These landscapes could be an indication of fake suppliers with poor capacity of delivering public goods and services. However, checking thousands of landscapes in order to find these fake suppliers would be a very expensive task. Our objective then is to discover what are the possible groups of scenes involving government suppliers, given that these images were not previously labeled, as automatically as possible. For that reason, we used Places CNN, a pretrained convolutional neural network for scene recognition presented by Zhou et al., which was trained on 205 scene categories with 2.5 million images, for scene recognition on Brazilian Government Suppliers.
Rodrigo Peres Ferreira
Data acquisition from mobile sensors
Data acquisition from mobile sensors
Coursework project on data analysis. Using machine learning and android sensors data to predict whether gadget is located indoors or outdoors.
Matvey
ejerciciosBachi
ejerciciosBachi
Plantilla para crear ejercicios
Pablo