Using SAS Viya REST APIs with Python and R

SAS

課程信息

3,643 次近期查看

SAS Viya is an in-memory distributed environment used to analyze big data quickly and efficiently. In this course, you’ll learn how to use the SAS Viya APIs to take control of SAS Cloud Analytic Services from a Jupyter Notebook using R or Python. You’ll learn to upload data into the cloud, analyze data, and create predictive models with SAS Viya using familiar open source functionality via the SWAT package -- the SAS Scripting Wrapper for Analytics Transfer. You’ll learn how to create both machine learning and deep learning models to tackle a variety of data sets and complex problems. And once SAS Viya has done the heavy lifting, you’ll be able to download data to the client and use native open source syntax to compare results and create graphics.

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100% 在線

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完成時間大約為18 小時

英語（English）

字幕：法語（French）, （歐洲人講的）葡萄牙語, 俄語（Russian）, 英語（English）, 西班牙語（Spanish）

講師

Jordan Bakerman

Analytical Training Consultant

Education

18,932 個學生

4 門課程

Ari Zitin

Analytical Training Consultant

SAS Education

2,512 個學生

1 門課程

可分享的證書

完成後獲得證書

100% 在線

立即開始，按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

完成時間大約為18 小時

英語（English）

字幕：法語（French）, （歐洲人講的）葡萄牙語, 俄語（Russian）, 英語（English）, 西班牙語（Spanish）

提供方

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.

教學大綱 - 您將從這門課程中學到什麼

週

週 1

完成時間為 1 小時

Course Overview

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

完成時間為 1 小時

1 個視頻（總計 1 分鐘）, 4 個閱讀材料, 1 個測驗

1 個視頻

Course Overview55

4 個閱讀材料

Learner Prerequisites1分鐘

Using SAS® Viya® for Learners with This Course (Required)10分鐘

Course Information (Required)10分鐘

Using Forums and Getting Help5分鐘

完成時間為 2 小時

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.

完成時間為 2 小時

10 個視頻（總計 55 分鐘）

10 個視頻

SAS Approach to Open Source Integration2分鐘

Cloud Analytic Services2分鐘

Jupyter Notebooks and Open Source Development Interfaces2分鐘

SAS Scripting Wrapper for Analytics Transfer2分鐘

CAS Actions in SAS Viya2分鐘

Connecting to CAS and Reading in Data1分鐘

DataFrames and CAS Tables on the Clients and Server2分鐘

Advantages to Open Source Integration2分鐘

Demo: Getting Started with CAS and the R API18分鐘

Demo: Getting Started with CAS and the Python API18分鐘

5 個練習

Question 2.0110分鐘

Question 2.0210分鐘

Question 2.0310分鐘

Question 2.0410分鐘

SAS® Viya® and Open Source Integration Quiz30分鐘

週

週 2

完成時間為 4 小時

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.

完成時間為 4 小時

15 個視頻（總計 107 分鐘）

15 個視頻

Introduction to Predictive Modeling1分鐘

Data Partitioning: Preventing Overfitting2分鐘

Logistic Regression Models3分鐘

Support Vector Machines2分鐘

Decision Trees2分鐘

Ensemble of Trees2分鐘

Neural Network Models3分鐘

Autotuning Hyperparameters1分鐘

Model Performance Assessment2分鐘

Model Performance Charts: ROC and Lift2分鐘

Demo: Using the R API to Create and Assess Models26分鐘

Demo: Using the Python API to Create and Assess Models25分鐘

Demo: Creating a Gradient Boosting Model in SAS Studio7分鐘

Demo: Using R Functions and Looping for Efficient Coding11分鐘

Demo: Using Python Functions and Looping for Efficient Coding11分鐘

4 個練習

Question 3.0110分鐘

Question 3.0210分鐘

Question 3.0310分鐘

Machine Learning Quiz30分鐘

週

週 3

完成時間為 2 小時

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.

完成時間為 2 小時

9 個視頻（總計 48 分鐘）

9 個視頻

Text Analytics3分鐘

Natural and Formal Languages1分鐘

Processing Words1分鐘

Processing Context2分鐘

Processing Concepts1分鐘

Extracting Information from the Term-Document Matrix3分鐘

Word Embedding3分鐘

Demo: Using the R API to Explore Text Documents15分鐘

Demo: Using the Python API to Explore Text Documents15分鐘

3 個練習

Question 4.0110分鐘

Question 4.0210分鐘

Text Analytics Quiz30分鐘

完成時間為 3 小時

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.

完成時間為 3 小時

13 個視頻（總計 67 分鐘）

13 個視頻

Traditional Neural Networks1分鐘

Hidden Unit Activation Functions2分鐘

Weight Initialization1分鐘

Regularization Methods3分鐘

Nonlinear Optimization Algorithms (or Gradient-Based Learning)3分鐘

Processors for Analytics1分鐘

Deep Neural Networks (DNN) versus Recurrent Neural Networks (RNN)2分鐘

Recurrent Neural Network Architecture1分鐘

Improving RNN Models1分鐘

Gated Recurrent Unit (GRU)2分鐘

Long Short-Term Memory (LSTM)2分鐘

Demo: Deep Learning Sentiment Prediction Using the R API21分鐘

Demo: Deep Learning Sentiment Prediction Using the Python API21分鐘

3 個練習

Question 5.0110分鐘

Question 5.0210分鐘

Deep Learning Quiz30分鐘

週

週 4

完成時間為 3 小時

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.

完成時間為 3 小時

11 個視頻（總計 63 分鐘）

11 個視頻

Time Series Forecasting2分鐘

Model Performance and Assessment2分鐘

Weighted Averages1分鐘

Simple Exponential Smoothing2分鐘

ARIMAX Models and Stationarity1分鐘

Autoregressive and Moving Average Terms2分鐘

Forecasting with Recurrent Neural Networks43

Demo: Automatic Forecasting Using the R API8分鐘

Demo: Automatic Forecasting Using the Python API8分鐘

Demo: Deep Learning Forecasting Using the R API16分鐘

Demo: Deep Learning Forecasting Using the Python API16分鐘

4 個練習

Question 6.0110分鐘

Question 6.0210分鐘

Question 6.0310分鐘

Time Series Quiz30分鐘

完成時間為 2 小時

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.

完成時間為 2 小時

7 個視頻（總計 43 分鐘）

7 個視頻

Image Classification and Object Detection2分鐘

Convolutional Neural Networks for Image Classification1分鐘

Convolution Layers3分鐘

Pooling Layers1分鐘

Fully Connected and Output Layers59

Demo: Classifying Color Images Using the R API16分鐘

Demo: Classifying Color Images Using the Python API16分鐘

2 個練習

Question 7.0110分鐘

Image Classification Quiz30分鐘

完成時間為 2 小時

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.

完成時間為 2 小時

4 個視頻（總計 29 分鐘）

4 個視頻

Recommender Systems2分鐘

Factorization Machines for Recommendation3分鐘

Demo: Modeling Sparse Data Using the R API11分鐘

Demo: Modeling Sparse Data Using the Python API11分鐘

2 個練習

Question 8.0110分鐘

Factorization Machines Quiz30分鐘

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Using SAS Viya REST APIs with Python and R