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英语(English)

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英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间为 1 小时

Course Overview

In this module, you meet the instructor and learn about course logistics, such as how to access the software for this course.

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1 个视频 (总计 1 分钟), 4 个阅读材料, 1 个测验
1 个视频
4 个阅读材料
Learner Prerequisites1分钟
Using SAS® Viya® for Learners with This Course (Required)10分钟
Course Information (Required)10分钟
Using Forums and Getting Help5分钟
完成时间为 2 小时

SAS® Viya® and Open Source Integration

In this module you learn about the analytical processing engine behind SAS Viya, the Cloud Analytic Services server. You also learn how to submit data processing commands to SAS Viya from the open source languages R and Python.

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10 个视频 (总计 55 分钟), 6 个测验
10 个视频
SAS Scripting Wrapper for Analytics Transfer2分钟
CAS Actions in SAS Viya2分钟
Connecting to CAS and Reading in Data1分钟
DataFrames and CAS Tables on the Clients and Server2分钟
Advantages to Open Source Integration2分钟
Demo: Getting Started with CAS and the R API18分钟
Demo: Getting Started with CAS and the Python API18分钟
5 个练习
Question 2.0110分钟
Question 2.0210分钟
Question 2.0310分钟
Question 2.0410分钟
SAS® Viya® and Open Source Integration Quiz30分钟
2
完成时间为 4 小时

Machine Learning

In this module you learn how to use R and Python to create, optimize, and assess SAS Viya predictive models. You also learn how to use R and Python to efficiently manage the creation and assessment of these models.

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15 个视频 (总计 107 分钟), 8 个测验
15 个视频
Support Vector Machines2分钟
Decision Trees2分钟
Ensemble of Trees2分钟
Neural Network Models3分钟
Autotuning Hyperparameters1分钟
Model Performance Assessment2分钟
Model Performance Charts: ROC and Lift2分钟
Demo: Using the R API to Create and Assess Models26分钟
Demo: Using the Python API to Create and Assess Models25分钟
Demo: Creating a Gradient Boosting Model in SAS Studio7分钟
Demo: Using R Functions and Looping for Efficient Coding11分钟
Demo: Using Python Functions and Looping for Efficient Coding11分钟
4 个练习
Question 3.0110分钟
Question 3.0210分钟
Question 3.0310分钟
Machine Learning Quiz30分钟
3
完成时间为 2 小时

Text Analytics

In this module you learn how natural language processing is used to analyze collections of text documents. You also learn how to turn blocks of unstructured text into numeric inputs suitable for predictive modeling.

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9 个视频 (总计 48 分钟), 5 个测验
9 个视频
Processing Context2分钟
Processing Concepts1分钟
Extracting Information from the Term-Document Matrix3分钟
Word Embedding3分钟
Demo: Using the R API to Explore Text Documents15分钟
Demo: Using the Python API to Explore Text Documents15分钟
3 个练习
Question 4.0110分钟
Question 4.0210分钟
Text Analytics Quiz30分钟
完成时间为 3 小时

Deep Learning

In this module you learn how deep learning methods extend traditional neural network models with new options and architectures. You also learn how recurrent neural networks are used to model sequence data like time series and text strings, and how to create these models using R and Python APIs for SAS Viya.

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13 个视频 (总计 67 分钟), 5 个测验
13 个视频
Regularization Methods3分钟
Nonlinear Optimization Algorithms (or Gradient-Based Learning)3分钟
Processors for Analytics1分钟
Deep Neural Networks (DNN) versus Recurrent Neural Networks (RNN)2分钟
Recurrent Neural Network Architecture1分钟
Improving RNN Models1分钟
Gated Recurrent Unit (GRU)2分钟
Long Short-Term Memory (LSTM)2分钟
Demo: Deep Learning Sentiment Prediction Using the R API21分钟
Demo: Deep Learning Sentiment Prediction Using the Python API21分钟
3 个练习
Question 5.0110分钟
Question 5.0210分钟
Deep Learning Quiz30分钟
4
完成时间为 3 小时

Time Series

In this module you learn how to model time series using two popular methods, exponential smoothing and ARIMAX. You also learn how to use the R and Python APIs for SAS Viya to create forecasts using these classical methods and using recurrent neural networks for more complex problems.

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11 个视频 (总计 63 分钟), 6 个测验
11 个视频
Simple Exponential Smoothing2分钟
ARIMAX Models and Stationarity1分钟
Autoregressive and Moving Average Terms2分钟
Forecasting with Recurrent Neural Networks43
Demo: Automatic Forecasting Using the R API8分钟
Demo: Automatic Forecasting Using the Python API8分钟
Demo: Deep Learning Forecasting Using the R API16分钟
Demo: Deep Learning Forecasting Using the Python API16分钟
4 个练习
Question 6.0110分钟
Question 6.0210分钟
Question 6.0310分钟
Time Series Quiz30分钟
完成时间为 2 小时

Image Classification

In this module you learn how convolutional neural networks are used to classify images and how to use the R and Python APIs for SAS Viya to create convolutional neural networks.

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7 个视频 (总计 43 分钟), 4 个测验
7 个视频
Pooling Layers1分钟
Fully Connected and Output Layers59
Demo: Classifying Color Images Using the R API16分钟
Demo: Classifying Color Images Using the Python API16分钟
2 个练习
Question 7.0110分钟
Image Classification Quiz30分钟
完成时间为 2 小时

Factorization Machines

In this module you learn how factorization machines are used to create recommendation engines and how to build factorization machine models in SAS Viya using the R and Python APIs.

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4 个视频 (总计 29 分钟), 4 个测验
4 个视频
Demo: Modeling Sparse Data Using the Python API11分钟
2 个练习
Question 8.0110分钟
Factorization Machines Quiz30分钟

讲师

Avatar

Jordan Bakerman

Analytical Training Consultant
Education

Ari Zitin

Analytical Training Consultant
SAS Education

关于 SAS

Through innovative software and services, SAS empowers and inspires customers around the world to transform data into intelligence. SAS is a trusted analytics powerhouse for organizations seeking immediate value from their data. A deep bench of analytics solutions and broad industry knowledge keep our customers coming back and feeling confident. With SAS®, you can discover insights from your data and make sense of it all. Identify what’s working and fix what isn’t. Make more intelligent decisions. And drive relevant change....

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