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Recent articles
Identifying Personal Identifiable Information (PII) in Unstructured Data with Microsoft Presidio
Topics covered in this article: Ethics and responsible machine learning
In today’s digital age, organizations collect and store vast amounts of data about their customers, employees, and partners. This data often contains Personal Identifiable Information (PII). With the growing prevalence of data breaches and cyber attacks, protecting PII has become a critical concern for businesses and government agencies alike. In this article, Statistics Canada will take a detailed look at Microsoft Presidio and how it helps organizations in Canada comply with privacy laws.
Introduction to Privacy Enhancing Cryptographic Techniques: Secure Multiparty Computation
Topics covered in this article: Ethics and responsible machine learning
The increasing prevalence of technologies, such as cloud, mobile computing, machine learning (ML), and the Internet of Things (IoT), create opportunities for innovation and information sharing, but also create challenges for data security and privacy. These challenges have been amplified during the global pandemic, working from home has driven faster adoption of hybrid and cloud services. This situation has strained existing security capabilities and exposed gaps in data security (Lowans, 2020). Meanwhile, global data protection legislation is maturing, and every organization that processes personal data faces higher levels of privacy and non-compliance risks than ever before (Wonham, Fritsch, Xu, de Boer, & Krikken, 2020). As a result, privacy-enhanced computation techniques, which protect data while it is being used, have been gaining popularity.
Computer vision models: seed classification project
Topics covered in this article: Computer Vision
By collaborating with members from inter-departmental branches of government, the Artificial Intelligence Lab team at the Canadian Food Inspection Agency leverages state-of-the-art machine learning algorithms to provide data-driven solutions to real-world problems and drive positive change.
Continue reading: Computer vision models: seed classification project: Indigenous Communities Food Receipts Crowdsourcing with Optical Character Recognition
Other recent articles
Browse articles by topic
Computer vision
- Comparing Optical Character Recognition Tools for Text-Dense Documents vs. Scene Text
- Computer vision models: seed classification project
- Context modelling with transformers: Food recognition
- Extracting Temporal Trends from Satellite Images
- Greenhouse Detection with Remote Sensing and Machine Learning: Phase One
- Image Segmentation in Medical Imaging
- Indigenous Communities Food Receipts Crowdsourcing with Optical Character Recognition
- Reducing data gaps for training machine learning algorithms using a generalized crowdsourcing application
- Self Supervised Learning in Computer Vision: Image Classification
- Tackling Information Overload: How Global Affairs Canada's "Document Cracker" AI Application Streamlines Crisis Response Efforts
- The Rationale Behind Deep Neural Network Decisions
Data processing and engineering
- A new indicator of weekly aircraft movements
- An image is worth a thousand words: let your dashboard speak for you!
- Building an All-in-One Web Application for Data Science Using Python: An evaluation of the open-source tool Django
- Creating Compelling Data Visualizations
- Data Engineering in Rust
- Deploying your machine learning project as a service
- Designing a metrics monitoring and alerting system
- Extracting Public Value from Administrative Data: A method to enhance analysis with linked data
- Implementing MLOps with Azure
- Making data visualizations accessible to blind and visually impaired people
- MlFlow Tracking: An efficient way of tracking modeling experiments
- Non-Pharmaceutical Intervention and Reinforcement Learning
- The COVID-19 cloud platform for advanced analytics
- Writing a Satellite Imaging Pipeline, Twice: A Success Story
Predictive analytics
- Forecasting power consumption in remote northern Canadian communities
- From Exploring to Building Accurate Interpretable Machine Learning Models for Decision-Making: Think Simple, not Complex
- Modelling SARS-CoV-2 Dynamics to Forecast PPE Demand
- NRCan's Digital Accelerator: Revolutionizing the way Natural Resources Canada serves Canadians through digital innovation
- Unlocking the power of data synthesis with the starter gide on synthetic data for official statistics
- Use of Machine Learning for Crop Yield Prediction
Text analysis and generation
- A Use Case on Metadata Management
- Applied Machine Learning for Text Analysis Community of Practice: 2021 in review
- Bias Considerations in Bilingual Natural Language Processing
- Chatting About Chatbots: A review of the Chatbot Workshop
- Document Intelligence: The art of PDF information extraction
- Indigenous Communities Food Receipts Crowdsourcing with Optical Character Recognition
- Official Languages in Natural Language Processing
- Text Classification of Public Service Job Advertisements
- Topic Modelling and Dynamic Topic Modelling: A technical review
- Using data science and cloud-based tools to assess the economic impact of COVID-19
- Version Control with Git for Analytics Professionals
- 2021 Census Comment Classification
Ethics and responsible machine learning
- A Brief Survey of Privacy Preserving Technologies
- Explainable Machine Learning, Game Theory, and Shapley Values: A technical review
- Identifying Personal Identifiable Information (PII) in Unstructured Data with Microsoft Presidio
- Introduction to Privacy-Enhancing Cryptographic Techniques
- Introduction to Cryptographic Techniques: Trusted Execution Environment
- Introduction to Privacy Enhancing Cryptographic Techniques: Secure Multiparty Computation
- Privacy enhancing technologies: An overview of federated learning
- Privacy preserving technologies part three: Private statistical analysis and private text classification based on homomorpic encryption
- Privacy Preserving Technologies Part Two: Introduction to Homomorphic Encryption
- Protected workloads on public cloud
- Responsible use of automated decision systems in the federal government
- Responsible use of machine learning at Statistics Canada
Other
- Production level code in Data Science
- Celebrating women and girls in science: An interview with Dr. Sevgui Erman
- Co-op student explores the power of Big Data
- Data Science Network Newsletter product feedback survey
- Developing Competency Profiles to Shape Data Science in the Public Service
- Developments in machine learning series: Issue three
- Developments in Machine Learning Series: Issue two
- Developments in Machine Learning Series: Series one
- First Data Science Network Directors' Committee Meeting
- Low Code UI with Plotly Dash
- Ottawa to hold World Statistics Congress in July 2023
- The Data Science Network newsletter turns one!