Udacity Machine Learning Nanodegree Projects
Project 1 - Predicting Boston Housing Prices
Model Evaluation and Validation
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Built a model to predict the value of a given house in the Boston real estate market (standard dataset) using various statistical analysis tools.
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Identified the best price that a client can sell their house using machine learning techniques.
Project 2 - Building a Student Intervention System
Supervised Learning
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Trained and tested several supervised machine learning models on a given dataset to predict how likely a high school student is to pass.
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Selected the best model based on relative accuracy and efficiency.
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Classifiers trained and tested include Decision Trees, Support Vector Machines (SVMs) and K-Nearest Neighbors (k-NN).
Project 3 - Explore the Clusters in a Dataset
Unsupervised Learning
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Reviewed unstructured data to understand the patterns and natural categories that the data fits into.
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Used multiple algorithms (PCA, ICA and clustering) and compared and contrasted their results both empirically and theoretically.
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Made predictions about the natural categories of multiple types in a dataset, then checked these predictions against the result of unsupervised analysis.
Project 4 - Train a Smartcab How to Drive
Reinforcement Learning
- Applied reinforcement learning to build a simulated vehicle navigation agent. This project involved modeling a complex control problem in terms of limited available inputs, and designing a scheme to automatically learn an optimal driving strategy based on rewards and penalties.