SAS Institute Of Management Studies - Using SAS Viya REST APIs with Python and R 

Course Overview

Learner Prerequisites

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

Course Information (Required)

Using Forums and Getting Help

SAS Approach to Open Source Integration

Cloud Analytic Services

Jupyter Notebooks and Open Source Development Interfaces

SAS Scripting Wrapper for Analytics Transfer

CAS Actions in SAS Viya

Connecting to CAS and Reading in Data

DataFrames and CAS Tables on the Clients and Server

Advantages to Open Source Integration

Demo: Getting Started with CAS and the R API

Demo: Getting Started with CAS and the Python API

Question 2.01

Question 2.02

Question 2.03

Question 2.04

SAS® Viya® and Open Source Integration Quiz

Introduction to Predictive Modeling

Data Partitioning: Preventing Overfitting

Logistic Regression Models

Support Vector Machines

Decision Trees

Ensemble of Trees

Neural Network Models

Autotuning Hyperparameters

Model Performance Assessment

Model Performance Charts: ROC and Lift

Demo: Using the R API to Create and Assess Models

Demo: Using the Python API to Create and Assess Models

Demo: Creating a Gradient Boosting Model in SAS Studio

Demo: Using R Functions and Looping for Efficient Coding

Demo: Using Python Functions and Looping for Efficient Coding

Question 3.01

Question 3.02

Question 3.03

Machine Learning Quiz

Text Analytics

Natural and Formal Languages

Processing Words

Processing Context

Processing Concepts

Extracting Information from the Term-Document Matrix

Word Embedding

Demo: Using the R API to Explore Text Documents

Demo: Using the Python API to Explore Text Documents

Question 4.01

Question 4.02

Text Analytics Quiz

Traditional Neural Networks

Hidden Unit Activation Functions

Weight Initialization

Regularization Methods

Nonlinear Optimization Algorithms (or Gradient-Based Learning)

Processors for Analytics

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

Recurrent Neural Network Architecture

Improving RNN Models

Gated Recurrent Unit (GRU)

Long Short-Term Memory (LSTM)

Demo: Deep Learning Sentiment Prediction Using the R API

Demo: Deep Learning Sentiment Prediction Using the Python API

Question 5.01

Question 5.02

Deep Learning Quiz

Time Series Forecasting

Model Performance and Assessment

Weighted Averages

Simple Exponential Smoothing

ARIMAX Models and Stationarity

Autoregressive and Moving Average Terms

Forecasting with Recurrent Neural Networks

Demo: Automatic Forecasting Using the R API

Demo: Automatic Forecasting Using the Python API

Demo: Deep Learning Forecasting Using the R API

Demo: Deep Learning Forecasting Using the Python API

Question 6.01

Question 6.02

Question 6.03

Time Series Quiz

Image Classification and Object Detection

Convolutional Neural Networks for Image Classification

Convolution Layers

Pooling Layers

Fully Connected and Output Layers

Demo: Classifying Color Images Using the R API

Demo: Classifying Color Images Using the Python API

Question 7.01

Image Classification Quiz

Recommender Systems

Factorization Machines for Recommendation

Demo: Modeling Sparse Data Using the R API

Demo: Modeling Sparse Data Using the Python API

Question 8.01

Factorization Machines Quiz