Use Neural Network to predicting daily bike rental ridership.

Implement a controller to keep a simulated vehicle in its lane. For an extra challenge, use computer vision techniques to identify the lane lines and estimate the cross-track error.

Implement a particle filter to take real-world data and localize a lost vehicle.

Fuse noisy lidar and radar data together to track a pedestrian.

Learned about deep neural networks and convolutional neural networks to clone driving behavior. You will train, validate and test a model using Keras. The model will output a steering angle to an a…

Learned about deep neural networks and convolutional neural networks to classify traffic signs. You will train a model so it can decode traffic signs from natural images by using the German Traffic…

Write a software pipeline to detect vehicles in a video

Write a software pipeline to identify the lane boundaries in a video.

One of the first things we would like to do in developing a self-driving car is to automatically detect lane lines using an algorithm. In this project we will detect lane lines in images using Pyth…

This cheat sheet includes most function in SQL, enough for general data administration based on SQL.

Answered interview questions about goal, project, coding and algorithm.

Created a data visualization from a data set that tells a story or highlights trends or patterns in the data. Used either dimple.js or d3.js to create the visualization.

Played detective and put machine learning skills to use by building an algorithm to identify Enron Employees who may have committed fraud based on the public Enron financial and email dataset.

Use R and apply exploratory data analysis techniques to explore a selected data set from red wine for distributions, outliers, and anomalies.

Used descriptive statistics and a statistical test to analyze the Stroop effect, a classic result of experimental psychology. Gave you a good intuition for the data and use statistical inference to…

Investigated a dataset from Titanic survivors by NumPy and Pandas. Go through the entire data analysis process, started by posing a question and finished by sharing my findings.

Downloaded map of San Jose from openStreermap and used data munging techniques, such as assessing the quality of the data for validity, accuracy, completeness, consistency and uniformity, to clean …