miguel75an Goto Github PK
Name: Miguel Dominguez
Type: User
Name: Miguel Dominguez
Type: User
Machine Learning: Building an AdaBoosting model using Decision Trees as weak learners.
Machine Learning: Experimenting with the Adaline model using different number of features from the Iris Flower Dataset. Finding accuracy and discussing the significance of features, variance and bias.
An unpleasant bot to talk to...for some reason
DataStructure: We create a bag class that uses nodes for each of its elements. Head and tail pointers. Linked Lists.
A look at 3 algorithms for basic sorting.
Project
A simple counter implemented with React
Data Science: Implementing SVM models against Logistic Regression models. Pick data set.
Machine Learning: Building Decision trees to classify data. Visuals to explore the depth of the trees and class leaves.
Experimenting with nyc_restaurants.csv dataset
Updated sign up and login page that connects to the database. Redirects to fbi page
A project built with React to implement a simple weather app. The app displays the high and low temperatures for five days, the current weather condition, the time, a dynamic weather icon and a gradient background.
Capstone I - Fall 2017 - Wei
A place to find colors by either Hexadecimal representations or RGB levels.
A really mini game where a hungry penguin tries to eat a fish village. But octo and crab will try to fight back.
Small project using React to create tool-tips for Japanese characters and words. As well, we make use of the <ruby> and <rt> tags and use them in a React class to implement furigana readings.
A game, in development
Playing with layered game objects, new movement mechanics and interactions
Files following the Pandas tutorial from Data School in Youtube
Data Science: Implementing LDA and comparing it with PCA
Machine Learning: We apply models of logistic regression to training data and compare our results with test data. We plot bar graphs. Finally, we play with the number of iterations for the models and regularization.
A lottery simulator which can either generate random numbers or accept the user numbers. If the input numbers match the winning numbers then the user gains money.
Matlab files related to numerical issues such as interpolation.
Machine Learning: Implement the Perceptron model and plot the linear decision boundary for linearly separable classes and attempt to plot it for non-linearly separable classes. Iris Flower dataset used.
Machine Learning: Using Regularization with different parameters. Add power weights.
Program checks for primality using the square root method.
Machine Learning: Building Random Forests with Decision Trees using different depths and forest sizes. As well, learning more about bootstrapping and out-of-bag scores.
Machine Learning: Implementing regression models
Initial scripts for object manipulation.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.