Information science
Resource Information
The concept Information science represents the subject, aboutness, idea or notion of resources found in San Francisco Public Library.
The Resource
Information science
Resource Information
The concept Information science represents the subject, aboutness, idea or notion of resources found in San Francisco Public Library.
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- Information science
265 Items that share the Concept Information science
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- A journey into data science : earning the white coat
- A policy-driven information exchange network
- A practical guide for informationists : supporting research and clinical practice
- Appuru teikoku no shōtai
- Azure AI Gallery & Azure Machine Learning : Cortana Intelligence Competitions
- Azure AI Gallery & Azure Machine Learning : Create a Collection in Azure AI Gallery
- Azure AI Gallery & Azure Machine Learning : Create a New Deployment using Azure AI Gallery
- Azure AI Gallery & Azure Machine Learning : Create a New Experiment from an Example
- Azure AI Gallery & Azure Machine Learning : Custom Modules from Azure AI Gallery
- Azure AI Gallery & Azure Machine Learning : Exercise: Use Azure AI Gallery
- Azure AI Gallery & Azure Machine Learning : Import Experiment from Azure AI Gallery
- Azure AI Gallery & Azure Machine Learning : Jupyter Notebooks from Azure AI Gallery
- Azure AI Gallery & Azure Machine Learning : Overview of Azure AI Gallery
- Azure AI Gallery & Azure Machine Learning : Use Custom Modules from Azure AI Gallery
- Azure AI Gallery & Azure Machine Learning : Use Sample Datasets in Azure Machine Learning Studio
- Azure AI Gallery & Azure Machine Learning : Use Tutorials in Azure AI Gallery
- Consume Models & APIs Using Azure Machine Learning Studio : Authorization Key
- Consume Models & APIs Using Azure Machine Learning Studio : Azure API Management
- Consume Models & APIs Using Azure Machine Learning Studio : Batch Execution Service
- Consume Models & APIs Using Azure Machine Learning Studio : Batch Execution Service Web App Templates
- Consume Models & APIs Using Azure Machine Learning Studio : Computer Vision APIs
- Consume Models & APIs Using Azure Machine Learning Studio : Consume Language APIs
- Consume Models & APIs Using Azure Machine Learning Studio : Excel Add-in for Web Service
- Consume Models & APIs Using Azure Machine Learning Studio : Exercise: Consuming a Web Service
- Consume Models & APIs Using Azure Machine Learning Studio : Publishing to Azure AI Gallery
- Consume Models & APIs Using Azure Machine Learning Studio : REST APIs
- Consume Models & APIs Using Azure Machine Learning Studio : Recommendations Solution Template
- Consume Models & APIs Using Azure Machine Learning Studio : Request-Response Service (RRS)
- Consume Models & APIs Using Azure Machine Learning Studio : Request-Response Service Web App Templates
- Consume Models & APIs Using Azure Machine Learning Studio : Web Service Connection
- Consume Models & APIs Using Azure Machine Learning Studio : Web Services from Excel
- Data Cleanup with Azure Machine Learning Studio : Applying Filters
- Data Cleanup with Azure Machine Learning Studio : Clip Values
- Data Cleanup with Azure Machine Learning Studio : Counts and Features
- Data Cleanup with Azure Machine Learning Studio : Duplicate Data
- Data Cleanup with Azure Machine Learning Studio : Exercise: Clean Datasets for Learning
- Data Cleanup with Azure Machine Learning Studio : Grouping Data
- Data Cleanup with Azure Machine Learning Studio : Missing Data
- Data Cleanup with Azure Machine Learning Studio : Normalization
- Data Cleanup with Azure Machine Learning Studio : SQL Transformations
- Data Cleanup with Azure Machine Learning Studio : Synthetic Minority Oversampling Technique (SMOTE)
- Data Science Essentials : Aggregating Data
- Data Science Essentials : Basic Data Gathering
- Data Science Essentials : Basic Data Science Math
- Data Science Essentials : Changing CSV Delimiters
- Data Science Essentials : Chi-Square
- Data Science Essentials : Choose a Machine Learning Method
- Data Science Essentials : Concatenating Log Files
- Data Science Essentials : Confidence Intervals
- Data Science Essentials : Connecting to Remote Data
- Data Science Essentials : Continuous Probability Distributions
- Data Science Essentials : Convert Dates to ISO 8601
- Data Science Essentials : Converting CSV to JSON
- Data Science Essentials : Converting CSV to SQL
- Data Science Essentials : Converting Dates
- Data Science Essentials : Converting Numbers
- Data Science Essentials : Converting SQL to CSV
- Data Science Essentials : Converting XML to JSON
- Data Science Essentials : Copying Remote Data
- Data Science Essentials : Correlation Versus Causation
- Data Science Essentials : Count Word Frequencies in a Classic Book
- Data Science Essentials : Counting Words
- Data Science Essentials : Create a Scatter Plot
- Data Science Essentials : Creating Bar Charts
- Data Science Essentials : Creating Box Plots
- Data Science Essentials : Creating Histograms
- Data Science Essentials : Creating Interactive Plots
- Data Science Essentials : Creating Network Visualizations
- Data Science Essentials : Creating Scatter Plots
- Data Science Essentials : Creating a Bubble Plot
- Data Science Essentials : Cull Old Data
- Data Science Essentials : Data Communication
- Data Science Essentials : Data Filtering Techniques and Tools
- Data Science Essentials : Data Formation
- Data Science Essentials : Data Science Pipeline
- Data Science Essentials : Data Science Terminology
- Data Science Essentials : Data Science Tools
- Data Science Essentials : Defining Overfitting
- Data Science Essentials : Defining Underfitting
- Data Science Essentials : Denormalizing Data
- Data Science Essentials : Determining Word Frequencies
- Data Science Essentials : Discrete Probability Distributions
- Data Science Essentials : Documenting Data Science
- Data Science Essentials : Dropping Duplicate Data
- Data Science Essentials : Effective Communication and Visualization
- Data Science Essentials : Estimators
- Data Science Essentials : Explore Your Data Science Needs
- Data Science Essentials : Exploring CSV Data
- Data Science Essentials : Exploring CSV Statistics
- Data Science Essentials : Exploring Directory Trees
- Data Science Essentials : Exploring HTML Tables
- Data Science Essentials : Extracting HTML Data
- Data Science Essentials : Extracting Legacy Data from dBASE Tables
- Data Science Essentials : Extracting Spreadsheet Data with agate
- Data Science Essentials : Extracting Spreadsheet Data with in2csv
- Data Science Essentials : Extracting Text from PDF Files
- Data Science Essentials : Filtering CSV Data
- Data Science Essentials : Filtering HTTP Headers
- Data Science Essentials : Filtering PDF Files
- Data Science Essentials : Filtering for Invalid Data
- Data Science Essentials : Finding Repeated Records
- Data Science Essentials : Finding the Top Rows
- Data Science Essentials : Gathering Metadata
- Data Science Essentials : Gathering Web Data
- Data Science Essentials : Homogenizing Rows
- Data Science Essentials : Hypothesis Tests
- Data Science Essentials : Identify Data Sets by Type
- Data Science Essentials : Identifying Outliers in Data
- Data Science Essentials : Introduction to Bayes Theorem
- Data Science Essentials : Introduction to Errors
- Data Science Essentials : Introduction to Probability
- Data Science Essentials : Introduction to Supervised Learning
- Data Science Essentials : Introduction to Unsupervised Learning
- Data Science Essentials : Joining CSV Data
- Data Science Essentials : K-means Clustering
- Data Science Essentials : Linear Algebra Matrix Decomposition
- Data Science Essentials : Linear Algebra Matrix Math
- Data Science Essentials : Linear Algebra Vector Math
- Data Science Essentials : Merge Two CSV Documents into One
- Data Science Essentials : Merging XML Data
- Data Science Essentials : Normalizing Data
- Data Science Essentials : OCR JPEG Images
- Data Science Essentials : Parsing robots.txt
- Data Science Essentials : Pivoting Data Tables
- Data Science Essentials : Plotting Line Graphs
- Data Science Essentials : Plotting from the Command Line
- Data Science Essentials : Presenting Data
- Data Science Essentials : Processing Date Formats
- Data Science Essentials : Querying CSV Data
- Data Science Essentials : Replacing Values with sed
- Data Science Essentials : Rounding Numbers
- Data Science Essentials : Sampling Data
- Data Science Essentials : Sampling Distributions
- Data Science Essentials : Simpson's Paradox
- Data Science Essentials : Sorting Text Files
- Data Science Essentials : Statistical Measures
- Data Science Essentials : Support Vector Machines (SVM)
- Data Science Essentials : Synchronizing Remote Data
- Data Science Essentials : Taking Random Samples
- Data Science Essentials : Understanding Dummy Variables
- Data Science Essentials : Understanding Linear Regression
- Data Science Essentials : Understanding Logistic Regression
- Data Science Essentials : Using Cluster Validation
- Data Science Essentials : Using K-folds Cross Validation
- Data Science Essentials : Using Naive Bayes Classification
- Data Science Essentials : Using Neural Networks
- Data Science Essentials : Using Principal Component Analysis
- Data Science Essentials : Visual Data Exploration
- Data Science Essentials : What is Big Data
- Data Science Essentials : What is Data Science
- Data Science Essentials : What is Data Wrangling
- Data Science Essentials : What is Machine Learning
- Data Science Essentials : Working with Decision Trees
- Data Science Essentials : Working with Email Headers
- Data Science Essentials : Working with Events
- Data Science Essentials : Working with HTTP Headers
- Data Science Essentials : Working with JPEG Headers
- Data Science Essentials : Working with Linux Log Files
- Data Science Essentials : Working with Predictors
- Data Science Essentials : Working with Probability
- Data science for business : what you need to know about data mining and data-analytic thinking
- Data science strategy
- Deploying Models with Azure Machine Learning Studio : Converting to a Predictive Experiment
- Deploying Models with Azure Machine Learning Studio : Deploying Web Services with Web Service Parameters
- Deploying Models with Azure Machine Learning Studio : Deploying a Classic Web Service
- Deploying Models with Azure Machine Learning Studio : Deploying a New Web Service
- Deploying Models with Azure Machine Learning Studio : Exercise: Deploying a Web Service
- Deploying Models with Azure Machine Learning Studio : Preparing an Experiment for Deployment
- Deploying Models with Azure Machine Learning Studio : Testing a Web Service
- Deploying Models with Azure Machine Learning Studio : Using Import and Export Modules
- Deploying Models with Azure Machine Learning Studio : Using Language Understanding Intelligent Service
- Deploying Models with Azure Machine Learning Studio : Using Train Matchbox Recommender
- Documentación de las ciencias de la información
- Doing data science
- Importing and Exporting in Azure Machine Learning Studio : Exercise: Importing and Exporting Data
- Importing and Exporting in Azure Machine Learning Studio : Exporting Intermediate Data to a Dataset
- Importing and Exporting in Azure Machine Learning Studio : Exporting to Azure Blob Storage
- Importing and Exporting in Azure Machine Learning Studio : Exporting to Azure SQL Database
- Importing and Exporting in Azure Machine Learning Studio : Exporting via Hive Queries
- Importing and Exporting in Azure Machine Learning Studio : Importing Data from On-premises SQL Server Database
- Importing and Exporting in Azure Machine Learning Studio : Importing from Azure Blob Storage
- Importing and Exporting in Azure Machine Learning Studio : Importing from Azure SQL Database
- Importing and Exporting in Azure Machine Learning Studio : Importing from Azure Table
- Importing and Exporting in Azure Machine Learning Studio : Importing from Hive Queries
- Importing and Exporting in Azure Machine Learning Studio : Importing from a Web Site with HTTP
- Introduction to Azure Machine Learning : Comparing Azure Machine Learning Studio Algorithms
- Introduction to Azure Machine Learning : Creating a Jupyter Notebook
- Introduction to Azure Machine Learning : Creating a Workspace
- Introduction to Azure Machine Learning : Defining Features
- Introduction to Azure Machine Learning : Exercise: Creating an Experiment
- Introduction to Azure Machine Learning : Getting Data
- Introduction to Azure Machine Learning : Managing a Workspace
- Introduction to Azure Machine Learning : Preparing Data
- Introduction to Azure Machine Learning : Scoring and Evaluating
- Introduction to Azure Machine Learning : Splitting Data and Applying ML Algorithms
- Introduction to Azure Machine Learning : Using the R Programming Language
- Introduction to Azure Machine Learning : What Is Azure Machine Learning Studio?
- Introduction to Azure Machine Learning : What Is Machine Learning?
- Introduction to Azure Machine Learning : Working with Azure Resource Manager (ARM)
- Introduction to information science
- Knowledge management tools
- Library and information science : special issue for the coming-of-age anniversary of SLIS
- Library hi tech
- Microsoft Cognitive Toolkit & Azure Machine Learning : Build a Neural Network
- Microsoft Cognitive Toolkit & Azure Machine Learning : Configure a Multiclass Neural Network
- Microsoft Cognitive Toolkit & Azure Machine Learning : Configure a Two-class Neural Network
- Microsoft Cognitive Toolkit & Azure Machine Learning : Exercise: Build Neural Networks
- Microsoft Cognitive Toolkit & Azure Machine Learning : Feed Forward Neural Network
- Microsoft Cognitive Toolkit & Azure Machine Learning : Microsoft Cognitive Toolkit (CNTK)
- Microsoft Cognitive Toolkit & Azure Machine Learning : Microsoft Cognitive Toolkit (CNTK) for Python
- Microsoft Cognitive Toolkit & Azure Machine Learning : Multiclass Neural Network
- Microsoft Cognitive Toolkit & Azure Machine Learning : N-Series Virtual Machines
- Microsoft Cognitive Toolkit & Azure Machine Learning : Neural Network Overview
- Microsoft Cognitive Toolkit & Azure Machine Learning : Two-class Neural Network
- National strategic overview for quantum information science
- Open source software
- Optimize & Validate Models in Azure Machine Learning Studio : Classification Models
- Optimize & Validate Models in Azure Machine Learning Studio : Clustering Models
- Optimize & Validate Models in Azure Machine Learning Studio : Cross Validate Model
- Optimize & Validate Models in Azure Machine Learning Studio : Evaluate Model
- Optimize & Validate Models in Azure Machine Learning Studio : Evaluate Recommender
- Optimize & Validate Models in Azure Machine Learning Studio : Exercise: Optimize and Validate Models
- Optimize & Validate Models in Azure Machine Learning Studio : Optimize Hyperparameters
- Optimize & Validate Models in Azure Machine Learning Studio : Optimize Parameters
- Optimize & Validate Models in Azure Machine Learning Studio : Parameter Sweep
- Optimize & Validate Models in Azure Machine Learning Studio : Regression Models
- Optimize & Validate Models in Azure Machine Learning Studio : Sample Data
- Optimize & Validate Models in Azure Machine Learning Studio : Split Data
- Optimize & Validate Models in Azure Machine Learning Studio : Stacking Method
- Perspectives on Data Science for Software Engineering
- Perspectives, insights & priorities : 17 leaders speak freely of librarianship
- Programming of life
- Public knowledge, private ignorance : toward a library and information policy
- Pulp friction
- Research & writing skills success : in 20 minutes a day
- Research and development in the computer and information sciences
- Rethinking the library in the information age
- Second-hand knowledge : an inquiry into cognitive authority
- Summarize Data with Azure Machine Learning Studio : Binning and Grouping
- Summarize Data with Azure Machine Learning Studio : Compute Elementary Statistics
- Summarize Data with Azure Machine Learning Studio : Exercise: Summarize and Group Data
- Summarize Data with Azure Machine Learning Studio : External Packages for Python
- Summarize Data with Azure Machine Learning Studio : Group Categorical Values
- Summarize Data with Azure Machine Learning Studio : Import External R Packages
- Summarize Data with Azure Machine Learning Studio : Microsoft R
- Summarize Data with Azure Machine Learning Studio : Pearson's R test
- Summarize Data with Azure Machine Learning Studio : Python Notebooks
- Summarize Data with Azure Machine Learning Studio : Summarize Data Module
- Summarize Data with Azure Machine Learning Studio : Test Hypothesis Using t-Test Module
- The portable MLIS : insights from the experts
- The portable MLIS : insights from the experts
- Toward foundations of information science
- Transforming Data in Azure Machine Learning Studio : Adding Columns
- Transforming Data in Azure Machine Learning Studio : Adding Rows
- Transforming Data in Azure Machine Learning Studio : Create Features
- Transforming Data in Azure Machine Learning Studio : Exercise: Performing Data Transformation
- Transforming Data in Azure Machine Learning Studio : Feature Selection
- Transforming Data in Azure Machine Learning Studio : Indicator Values
- Transforming Data in Azure Machine Learning Studio : Merge datasets
- Transforming Data in Azure Machine Learning Studio : Metadata
- Transforming Data in Azure Machine Learning Studio : Principal Component Analysis (PCA)
- Transforming Data in Azure Machine Learning Studio : Subset of Columns
- Tu shu guan xue yü zi xun ke xue zhi tan tao : On library and information science
- When we are no more : how digital memory is shaping our future
- When we are no more : how digital memory is shaping our future
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.sfpl.org/resource/cBaA7-CfJok/" typeof="CategoryCode http://bibfra.me/vocab/lite/Concept"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.sfpl.org/resource/cBaA7-CfJok/">Information science</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.sfpl.org/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.sfpl.org/">San Francisco Public Library</a></span></span></span></span></div>
