Mathematica 10 Advanced Analysis Год выпуска: 2015 Производитель: Lynda Сайт производителя: lynda.com Автор: Curt Frye Продолжительность: 2:29 Тип раздаваемого материала: Видеоклипы Язык: Английский Описание: 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. Курс по "Математике 10" для опытных пользователей.
Содержание
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
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