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zbridge's Projects

behavioral_clone icon behavioral_clone

By observing human driving behavior on the road, vehicles complete their driving tasks on the road by learning the behavior.

build-a-data-science-web-app icon build-a-data-science-web-app

Using Python and Streamlit to build beautiful and interactive web apps with zero web development experience! We are going to load, explore, visualize and interact with data, and generate dashboards in less than 100 lines of Python code! We will accomplish it by completing each task in the project:

carnd-path-planning-project icon carnd-path-planning-project

The goal of this project is to build a path planner that creates smooth, safe trajectories for the car to follow. The highway track has other vehicles, all going different speeds, but approximately obeying the 50 MPH speed limit. The car transmits its location, along with its sensor fusion data, which estimates the location of all the vehicles on the same side of the road.

carnd_lanelines_p1 icon carnd_lanelines_p1

The goal of this first project was to create a simple pipeline to detect road lines in a frame taken from a roof-mounted camera. Being the very first project, the pipeline is necessarily very simple. No machine learning is involved - just computer vision and a lot of boring manual parameter tuning. :-)

cpp-capstone icon cpp-capstone

This is Tetris vedio game for the Capstone project in the Udacity C++ Nanodegree Program

extended_kelman_filter icon extended_kelman_filter

In this project you will utilize a kalman filter to estimate the state of a moving object of interest with noisy lidar and radar measurements. Passing the project requires obtaining RMSE values that are lower than the tolerance outlined in the project rubric.

sfnd_unscented_kalman_filter icon sfnd_unscented_kalman_filter

In this project We implement an Unscented Kalman Filter to estimate the state of multiple cars on a highway using noisy lidar and radar measurements. The main program can be built and ran by doing the following from the project top directory.

unscented-kalman-filter-highway-project icon unscented-kalman-filter-highway-project

In this project We implement an Unscented Kalman Filter to estimate the state of multiple cars on a highway using noisy lidar and radar measurements. The main program can be built and ran by doing the following from the project top directory.

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