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advertising_logistic_reg_project

This notebook looks at analyzing some user data from a company website. This company is looking to see if a model can be developed to determine if a user has actually clicked on an advertisement or not on the website. There are a few data visualizations and then a logistic model is created to help guide our data for a classification approach to determine a simple "yes" or "no" (or 0 and 1) for if a user did in fact click on an advertisement.

analyzing_911_calldata

This notebook looks at analyzing some 911 call data from the city of Montgomery County in Pennsylvania. There are a few data visualizations, some data cleansing and some column and row manipulations as well.

categorizing-neighborhood-restaurant-data-in-toronto-

This repository consists of a presentation, research paper and jupyter notebook discussing clustering patterns for Restaurants in the city of Toronto using a KMeans Clustering Algorithm

ecommerce_linear_regression_project

This notebook looks at analyzing some user data from a fictional E-commerce company operating out of New York City. There are a few data visualizations, some data cleansing and some column and row manipulations as well then we can answer some business questions using a simple linear regression model to help guide our data to a very clean model.

flatris-lab

github-directory

hands-on-machine-learning-textbook

This is a repository consisting of the 19 chapter jupyter notebooks from the textbook: Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow by Aurélien Géron. This textbook and its respective were worked on over the course of several months along side the end of chapter exercises in each sub folder. The original repository by the author can be found here: https://github.com/ageron/handson-ml2

handwrittennumbers_recognition_ml

This Repository contains a learning algorithm that learns how to read handwritten number in matlab/octave for a linear regression cost function implementation and neural network implementation for forward propogation. This project is part of Andrew Ng's Machine Learning course from Stanford University. Each file contains comments and explanations of the implementation. Something to note, weights for the neural network have already been assigned and for the handwritten numbers being read, we transformed these images from a jpeg image format into pixel matrices in octave This makes it so our code is much easier to implement.

ibm_coursera_week3_project

This repository contains three different files used for a project to use wikipedia data about geographical data to cluster common locations and create a geomap with those clusters. NOTE: This project uses my log in credentials from Foursquare to access common lat,lon and hotspot data for the area of toronto

neural-style-transfer

This project uses neural style transfer to combine two images together to create artistic images. This project consists of a jupyter notebook where all the code resides, a readme file, an MIT license, and images used throughout the project.

nn_classification_project_lendingclub

This notebook looks at analyzing some loan information from a kaggle dataset from LendingClub. The goal of this notebook is to create a classification neural network that is able to accurately predict whether an individual would recieve the laon they applied for or if it would be rejected. The reason for this is to determine if the individual would be able to pay back their loan to the lender so that the lender's investment will not be forfeit.

predictive_lstm_stock_market_project

This project consists of data visualization, data analysis, data cleansing and building a LSTM (Long Short Term Model) in the keras shell of TensorFlow from a stock market dataset from 85/100 of the companies in the NASDAQ 100 to map previous data and attempt to map future data. This project was completed in a Jupyter notebook in Python using common Data Science libraries

self-driving-picar

Welcome to the Self-Driving PiCar repository! This project aims to explore the exciting intersection of autonomous driving and Raspberry Pi technology. In this repository we will be developing a self-driving miniature car powered by a Raspberry Pi, integrating computer vision, machine learning, and robotics.

sunfounder_pca9685

SunFounder PCA9685 Python3 changes

sunfounder_picar

Smart Video Car Kit V2.0 for Raspberry Pi from SunFounder Forked from Sunfounder. Written in Python3 - Additional Edits

web_blog

Simple web-based blog to introduce Flask, HTML, CSS, Bootstrap, and Jinja2.