2015
Lynda
Curt Frye
2:29
English
This training course teaches analysts how to go beyond the basics of Mathematica 10 and start analyzing financial data, applying machine-learning algorithms, predicting and classifying data using linear and logistic regression, and analyzing relationships on social networks. Author Curt Frye also shows how to display maps, investigate data about different countries and time periods, visualize random data, and gain better insights from text. Using these techniques, you'll have the power and flexibility you need to dive deep into the information at hand and make good decisions for your organization.
Introduction
Welcome
What you should know before watching this course
Using the exercise files
1. Working with Geographic, Economic, and Other Data
Discovering the geographic position of an entity
Generating interesting and useful maps
Displaying statistical data about a country
Displaying statistical data about a city or territory
Discovering information on significant individuals
Returning data on historical periods
Analyzing word usage
2. Discovering and Displaying Financial Data
Returning the latest stock price for a company
Displaying the high, low, open, and close values for a stock
Graphing financial data using a candlestick chart
Displaying changes in a stock price over the past year
Displaying a list of currency symbols
Calculating the exchange rate between two currencies
Calculating the time value of money and adjusting for inflation
Discovering the effective interest rate of an investment
Calculating the present value of an annuity
3. Generating and Analyzing Time Series and Random Data
Creating and displaying a time series
Finding and displaying data within a time series window
Selecting a random value from a list of values
Generating and graphing a random walk process
Generating random values using different processes
4. Performing Social Network Analysis
Generating a random graph
Calculating centrality by counting direct links
Evaluating centrality by calculating betweenness
Identifying cliques in a graph
Calculating the shortest path between two points
Calculating reciprocity in a directed graph
5. Applying Machine Learning Algorithms to Data
Rescaling data to minimize bias
Classifying data based on existing rules
Classifying data by identifying rules through training data
Predicting output values using linear regression
Identifying clusters of data
6. Manipulating and Analyzing Textual Data
Importing a text file into Mathematica
Splitting a text string into words or sentences
Looking up words in dictionaries
Counting word occurrences within a string
Preparing text data for natural language processing
Performing sentiment analysis on text
Conclusion
Further resources
Download File Size:260.58 MB
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