ML-Investment
Scraping data sets from Yahoo Finance API using Python and Pandas, applying machine learning techniques and STREAMLIT to predict and visualize stock prices.
Tools and languages: Postgres SQL, Pandas, JavaScript, Machine Learning
Data Engineer who is passionate in Data analytics and Machine learning with a certificate in data analytics and visualization from the University of Toronto. More than 7 years of experience in control systems engineering. Team player who takes initiatives, enjoys solving problems and a strong communicator. Limitless ability to slice the elephant, proven experience in data pipelining and finds satisfaction in gleaning insights from data sets.
Longueuil, Qc, Canada
August 2014 - Present
Montreal, Qc, Canada
Jan 2011 - June 2012
Scraping data sets from Yahoo Finance API using Python and Pandas, applying machine learning techniques and STREAMLIT to predict and visualize stock prices.
Tools and languages: Postgres SQL, Pandas, JavaScript, Machine Learning
Utilizing Postgres SQL to help Pewlett Hackard to realize how many employees will be retiring this year and categorizing them by their title, as well as count the number of employees who qualify to be in the mentorship program to train new employees.
Tools and languages: Postgres SQL
Assess credit risk of applicants using supervised machine learning. Several different machine learning techniques such as SMOTE, SMOTEENN, RANDOM FOREST, EASY ENSEMBLE were applied, the models were assessed using accuracy score, precision and accuracy to choose the best technique that applies to this type of problem.
Tools and languages: Pandas library and Python
This project aims at analyzing data from many volunteers to identify the top 10 bacterial species in their belly buttons. These bacteria will help Improbable-Beef in manufacturing synthetic beef. A HTML/JavaScript page that displays a customized dashboard with a bar chart that identifies the type of bacteria, a gauge that displays the number of times a belly button is washed per week and a bubble chart that shows the abundance of specific bacteria per sample. The page is interactive and the user is able to use a drop down list to choose a specific volunteer, the information on that volunteer is displayed in a table and the gauges and graphs will adjust to the results of that specific volunteer.
PyBer company is conducting an analysis on data collected to examine the relation between different city type(urban, rural and suburban) and the number of drivers and riders, as well as the percentage of total fares riders and drivers by type of city. Analysis is to be concducted and visualizations are to be produced.
The purpose of this analysis is to obtain more information about temperature trends before opening the surf shop. Analyzing temperature data for the months of June and December in Oahu, in order to determine if the surf and ice cream shop business is sustainable year-round.
A prominent investment bank, is interested in offering a new cryptocurrency investment portfolio for its customers, but due to the large number exisiting cryptocurrencies, some work must be done to create a report that includes what cryptocurrencies are on the trading market and how they could be grouped to create a classification system for this new investment. Unsupervised machine learning is applied. Using K-means, the number of clusters was identified as 4. The clusters of the cryptocurrencies were visualized using 3D scatter plot. Finally, the total number of cois mined was also identified and visualized using a 2d sctter plot. The data is ready to be viewed by the bank and decisions can be made using these plots.
This project uses leaflet to map earthquakes, major earthquakes and the tectonic plat in the earth. It is a combination of java script (leaflet), HTML to showcase the map and CSS for formatting.
This project is designed to use java script to present a data file that contains UFO sightings in a HTML page. The user can also use some filters in the webpage to help narrow down search results. Bootstrap is used to give customize and give design to the webpage.
The project herein has the following main points using R programming language:
-Perform multiple linear regression analysis to identify which variables in the dataset predict the mpg of MechaCar prototypes.
-Collect summary statistics on the pounds per square inch (PSI) of the suspension coils from the manufacturing lots.
-Run t-tests to determine if the manufacturing lots are statistically different from the mean population.
-Design a statistical study to compare vehicle performance of the MechaCar vehicles against vehicles from other manufacturers.
This analysis is done in Tableau to understand, analyze and draw conclusions from a bike sharing service in the city of New York in order to apply these observations to the bike sharing service intended to be established in the city of Des Moines. This analysis is done using Tableau software.
