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- Project: Evaluating the Performance of Lexicon-based and Machine Learning Sentiment Analysis for Amazon reviews classification.
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- Final year project: Developing a Web Dashboard for analyzing Amazon's Laptop sales data.
- To know more about this project, visit Developing a Web Dashboard for analyzing Amazon's Laptop sales data
In my final Bachelor (Honours) in IT I worked in Sentiment Analysis using Python. I specifically developed a Web Dashboard for analyzing Amazon's Laptop sales data, mainly to perform a Sentiment Analysis on Amazon customer reviews.
- I have performed a Sentiment Analysis of Amazon customer reviews by using both, Lexicon-based and Machine Learning methods.
- Lexicon-based Sentiment Analysis: One of the purposes of this study is to evaluate different Sentiment Analysis approaches. That is why I performed a Lexicon-based Sentiment Analysis using two popular Python libraries: Textblob and Vader Sentiment.
- Machine Learning Sentiment Analysis: I have built a ML classifier for Sentiment Analysis using the Naive Bayes algorithm and an Amazon review dataset from Wang et al. (2010).It is important to notice that this is an extra result with respect to the initial objectives. I haven’t planned to carry out this studio. However, I realized that it was very beneficial to include another Sentiment Analysis approach. This has allowed me to evaluate and compare both approaches in terms of their performance.
- In addition, a Word Emotion Association Analysis has been also performed. This analysis complements the polarity analysis by adding more details about the kind of emotions or sentiments (joy, anger, disgust, etc.) in customer reviews. This analysis was performed by using the NRC Word-Emotion Association Lexicon.
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- Final year project: Supervised Machine Learning Models for Fake News Detection.
- To know more about this project, visit Supervised_Machine_Learning_for_Fake_News_Detection
In my final Bachelor in IT project, I worked in Text classification, specifically in Supervised Machine Learning for Fake News Detection using R. In this project, we have created a Supervised Machine Learning Model for Fake News Detection based on three different algorithms: Naive Bayes, Support Vector Machine, and Gradient Boosting (XGBoost). Basically, this ML model is able to determine with an accuracy of 79% if a News Article is Fake or Reliable. Fake in the sense of News Articles that were deliberately created in order to deceive and manipulate.
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- Specialty: Distributed information systems and networks.
- Final year study project: Design and Administration of a Wiki Web Application.
I have always had a strong interest in Computer Sciences. In fact, when I start my studies in the university, I had to choose between Computer Sciences and Geophysics.
During my studies in geophysics, I took courses in Fortran and C programming, and in Linux System Administration... and I had to program many times in Matlab (for example)... and thus I acquired computer skills.
The master's programme included courses of:
- Algorithms and Programming. I took courses in C programming, java and SQL
- We also received a training in database management
- Linux systems administration
- Networks administration.
Those are the areas I really appreciated, and in these areas is that I have my best computer skills, but there were other courses of course, like:
- VRML: Virtual Reality Modeling Language is a standard file format for representing 3-dimensional (3D) interactive vector graphics,
- XML: Extensible Markup Language is a markup language that defines a set of rules for encoding documents in a format that is both human-readable and machine-readable.
- PHP programming
Yes, they were basic courses because it was a one year master... and it was a master oriented to not computer professionals. But even if we were not computer professionals we had all computer skill. Because it was a requirement to enroll in that master. So the the courses had a good level I think so.
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No existe traducción en francés
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Algoritmo y programación (C, Java, VRML)
Base de Datos: SQL
Administración de sistemas operativos: Linux
Redes
VRML
XML
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- Specialty: Applied Petroleum Geoscience.
- Master thesis project (Excellence Honor Mention): Study of Pull up/Push down effects through seismic modelling, colombian plains.
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I got a master's degree in Petroleum geosciences. I dit this master because I wanted to focuses in oil exploration...
During this master, I took modules related to the oil exploration process.
I deepen my knowledge in areas such as:
- Seismic processing and modeling
- Petrophysics
- Seismic réservoir characterization
And I received a training in:
- Petroleum System Analysis
- Petroleum geology
These studies gave me the knowledge to understand how the oil industry works
These studies gave me an overview of how the oil industry works.
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Métodos avanzados de interpretación sísmica:
Petrofísica:
Tectónica de Placas:
Descripción sísmica de yacimientos:
Análisis de sistemas petroleros:
Geointegración petrolera:
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My master thesis at CGGVeritas
Creo que hoy en día la geofísica de exploración y producción debe enfocarse en pequeños detalles. Esto porque la exploración de hidrocarburos ya no requiere de un campo gigante para ser economicamente rentable, actualmente pequeñas acumulaciones pueden dar lugar a importantes beneficios para las compañías, pero para ello es indispensable ser detallista en los diversos pasos de exploración y producción. Por ejemplo, el campo de estudio de mi trabajo de maestría estaba compuesto por pequeñas acumulaciones; y en mi trabajo se trata un problema relacionado a la deformación de los reflectores a causa de variaciones laterales de velocidad, el trabajo concluye que estos problemas, podrían ser vitales para una apropiada cuantificación de las reservas.
Les vitesses de propagation des ondes sismiques
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Les vitesses de propagation des ondes sismiques.
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- Bachelor thesis project: Basic modelling of pre-stacked seismic data and its corresponding processing sequence, using Seismic Unix package.
Geophysics is a discipline that uses different areas of knowledge, such as physics, mathematics, and geology to study the internal constitution and history of the Earth.
The Geophysical engineering career at Simón Bolívar University is based on:
- A training in seismic exploration methods (acquisition, processing, inversion, and interpretation) and its direct application to the oil industry.
- The program also includes a basic training in gravimetric, magnetic and electrical exploration methods
- Some courses in geology.
But the career is oriented towards oil exploration because Venezuela is an oil-producing country.
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La Ingeniería Geofísica aplica distintas áreas del conocimiento tales como la Física, las Matemáticas y la Geología, al estudio de la constitución interna e historia de la Tierra.
La formación del Ingeniero Geofísico en la Universidad Simón Bolívar se cimenta en:
- Una preparación en métodos de exploración sísmica (adquisición, procesamiento, inversión e interpretación) y sus aplicaciones directas a la industria petrolera.
- Una preparación básica en métodos de exploración gravimétrica, magnética, y eléctrica
- Una cadena de cursos en Geología que sirven al futuro ingeniero en sus labores de interprete y geointegrador.
Ejemplos de aplicaciones de la Ingeniería Geofísica:
- En la exploración petrolera, los métodos de prospección sísmica permiten detectar las trampas que sirven de receptáculos a los hidrocarburos a profundidades que por otras vías sería imposible determinar.
- En la exploración minera los métodos gravimétricos y magnéticos permiten la evaluación del suelo y del subsuelo con el fin de ubicar y/o descubrir, ampliar y redefinir yacimientos minerales que no son visibles en superficie, además de que por estas mismas vías es posible establecer zonas de recursos minerales económicamente explotables.
- En la Ingeniería Civil la Geofísica permite estudiar las condiciones del subsuelo para el emplazamiento de obras de envergadura (presas, viaductos, edificios, carreteras etc.) y en la Agronomía permite definir posibles acuíferos utilizables ya sea para riego o para consumo humano.
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Simón Bolívar University and background in Mathematics/Physics
I'm an engineer from the most important scientific Venezuelan university, which is Simón Bolívar University; and really, I need to highlight the academic level and the quality of Simón Bolivar University. If you check now, Simón Bolívar University is still in a good place in the LatAm University Rankings; but the university has been widely affected by the difficult political situation in the country. I don't know if you have heard about the critical political and economical situation in Venezuela. But the fact is that in my time when I started my career, Simón Bolívar university was always in the top 10 of the best LatAm Universities with scientific and technological orientation.
I have a very good background in formal and pure sciences, like mathematic and physic. I followed 7 pure maths and 5 pure physics courses; without counting all the applied geophysical courses that I followed with a high content of mathematics, physics, or chemistry.
If you review the course content of an IT program you will find at most 2 mathematic courses. I really think that for an IT professional it is very important to have a good background in mathematic. For example, to be able to understand some computational concepts (functional programming for example) you need to have a good mathematical background.
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