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CIS 545: Big Data Analytics (Spring 2018)
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Assignment 0 |
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Getting Started.
This simple assignment gets you started with Docker and Jupyter, as well as our
course submission site.
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Assignment 1 |
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Data Wrangling.
Learn to read, save, combine, and clean data in Pandas and SQL. Integrate across sources. Conduct simple analyses of data.
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Assignment 2 |
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Big Data, Graph Data.
Learn to use Apache Spark. Traverse graph data. Compute measures of graph centrality. Recommend friends in a social network.
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Assignment 3 |
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The Cloud, Matrices, and Arrays.
Learn to use Spark on Elastic MapReduce. Perform computations over graphs and documents using NumPy.
Learn a bit about document vectors and information retrieval.
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Assignment 4 |
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Optimization, Search, and Clustering.
Learn algorithmic
primitives such as gradient-descent, search, genetic algorithms,
dynamic programming, and clustering. Along the way you'll build a
simple artificial neuron and learn about gene sequence alignment.
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Assignment 5 |
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Classification and TensorFlow.
Build a classifier using spam,
experimenting with different classifier methods and ensembles. Construct
a neural network in Google's TensorFlow.
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Assignment 6 |
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Tuning, Time-Series Data and Visualization.
Experiment with
tuning classifiers for detecting seizures in dog EEG data. Visualize
spatiotemporal activity from earthquakes.
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