corpus.blog
41554 blogs · [ { "id": "01a0874d-2063-72ad-b57a-de84589c9d9b", "title": "Privacy Evaluations for AI Systems", "url": "https://blog.kjamistan.com/privacy-evaluations-for-ai-systems.html", "published_at": "2026-09-02T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de84596c3620", "title": "Building an AI Privacy Router", "url": "https://blog.kjamistan.com/building-an-ai-privacy-router.html", "published_at": "2026-07-12T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de845974d4c5", "title": "AI Guardrails Explained", "url": "https://blog.kjamistan.com/ai-guardrails-explained.html", "published_at": "2026-06-17T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de845a4f4652", "title": "Using Synthetic Data for Privacy in AI/ML Systems", "url": "https://blog.kjamistan.com/using-synthetic-data-for-privacy-in-aiml-systems.html", "published_at": "2026-05-12T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de845acef2fe", "title": "Using Claude Code with Locally-Hosted models", "url": "https://blog.kjamistan.com/using-claude-code-with-locally-hosted-models.html", "published_at": "2026-04-06T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de845b849632", "title": "Practical AI Privacy: A 6-week online Maven masterclass", "url": "https://blog.kjamistan.com/practical-ai-privacy-a-6-week-online-maven-masterclass.html", "published_at": "2026-03-29T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de845c1bca7d", "title": "Differential Privacy Parameters, Accounting and Auditing in Deep Learning and AI", "url": "https://blog.kjamistan.com/differential-privacy-parameters-accounting-and-auditing-in-deep-learning-and-ai.html", "published_at": "2026-02-05T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de845c65ae47", "title": "Get your data local: Setting up Network Attached Storage (NAS) and your first steps in self-hosting", "url": "https://blog.kjamistan.com/get-your-data-local-setting-up-network-attached-storage-nas-and-your-first-steps-in-self-hosting.html", "published_at": "2026-01-30T08:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de845d2ba733", "title": "Building out my home AI Lab for private and local AI", "url": "https://blog.kjamistan.com/building-out-my-home-ai-lab-for-private-and-local-ai.html", "published_at": "2026-01-15T08:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de845df4fc27", "title": "Differential Privacy in Today's AI: What's so hard?", "url": "https://blog.kjamistan.com/differential-privacy-in-todays-ai-whats-so-hard.html", "published_at": "2026-01-05T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de845ea4aaad", "title": "Differential Privacy in Deep Learning", "url": "https://blog.kjamistan.com/differential-privacy-in-deep-learning.html", "published_at": "2025-11-09T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de845ec2a591", "title": "Attacks on Machine Unlearning: How Unlearned Models Leak Information", "url": "https://blog.kjamistan.com/attacks-on-machine-unlearning-how-unlearned-models-leak-information.html", "published_at": "2025-10-12T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de845f64d533", "title": "Machine Unlearning: How today's Unlearning is done", "url": "https://blog.kjamistan.com/machine-unlearning-how-todays-unlearning-is-done.html", "published_at": "2025-09-18T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de845f81c7fd", "title": "Machine unlearning: what is it?", "url": "https://blog.kjamistan.com/machine-unlearning-what-is-it.html", "published_at": "2025-08-12T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846036caf5", "title": "AI Risk and Threat Taxonomies", "url": "https://blog.kjamistan.com/ai-risk-and-threat-taxonomies.html", "published_at": "2025-08-04T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de84604afe57", "title": "Algorithmic-based Guardrails: External guardrail models and alignment methods", "url": "https://blog.kjamistan.com/algorithmic-based-guardrails-external-guardrail-models-and-alignment-methods.html", "published_at": "2025-07-27T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846062a49c", "title": "Blocking AI/ML Memorization with Software Guardrails", "url": "https://blog.kjamistan.com/blocking-aiml-memorization-with-software-guardrails.html", "published_at": "2025-07-10T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de8460c0b9b3", "title": "Defining Privacy Attacks in AI and ML", "url": "https://blog.kjamistan.com/defining-privacy-attacks-in-ai-and-ml.html", "published_at": "2025-06-11T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de8460ec80ed", "title": "Priveedly: your private and personal content reader and recommender", "url": "https://blog.kjamistan.com/priveedly-your-private-and-personal-content-reader-and-recommender.html", "published_at": "2025-01-22T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de8461a30630", "title": "Adversarial Examples Demonstrate Memorization Properties", "url": "https://blog.kjamistan.com/adversarial-examples-demonstrate-memorization-properties.html", "published_at": "2025-01-14T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846277804b", "title": "Differential Privacy as a Counterexample to AI/ML Memorization", "url": "https://blog.kjamistan.com/differential-privacy-as-a-counterexample-to-aiml-memorization.html", "published_at": "2025-01-01T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de8462a95a4f", "title": "How Memorization Happens: Overparametrized Models", "url": "https://blog.kjamistan.com/how-memorization-happens-overparametrized-models.html", "published_at": "2024-12-17T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de8462dec422", "title": "How memorization happens: Novelty", "url": "https://blog.kjamistan.com/how-memorization-happens-novelty.html", "published_at": "2024-12-08T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846371ed4c", "title": "How memorization happens: Repetition", "url": "https://blog.kjamistan.com/how-memorization-happens-repetition.html", "published_at": "2024-12-02T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de8464249ad4", "title": "Gaming Evaluation - The evolution of deep learning training and evaluation", "url": "https://blog.kjamistan.com/gaming-evaluation-the-evolution-of-deep-learning-training-and-evaluation.html", "published_at": "2024-11-25T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de8464a1d48f", "title": "Exploring new meadows", "url": "https://blog.kjamistan.com/exploring-new-meadows.html", "published_at": "2024-11-19T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de8464b904ba", "title": "Private and Personalized AI", "url": "https://blog.kjamistan.com/private-and-personalized-ai.html", "published_at": "2024-11-18T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de8464c7b9c8", "title": "Encodings and embeddings: How does data get into machine learning systems?", "url": "https://blog.kjamistan.com/encodings-and-embeddings-how-does-data-get-into-machine-learning-systems.html", "published_at": "2024-11-17T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de8465bdfd17", "title": "Machine Learning dataset distributions, history, and biases", "url": "https://blog.kjamistan.com/machine-learning-dataset-distributions-history-and-biases.html", "published_at": "2024-11-12T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de8465f036af", "title": "Deep learning memorization, and why you should care", "url": "https://blog.kjamistan.com/deep-learning-memorization-and-why-you-should-care.html", "published_at": "2024-11-03T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de8466832ebc", "title": "A Deep Dive into Memorization in Deep Learning", "url": "https://blog.kjamistan.com/a-deep-dive-into-memorization-in-deep-learning.html", "published_at": "2024-11-02T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de8466d4b21d", "title": "Building a Privacy-First Newsletter", "url": "https://blog.kjamistan.com/building-a-privacy-first-newsletter.html", "published_at": "2023-03-12T08:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de8467025a20", "title": "Joining Dropout Labs!", "url": "https://blog.kjamistan.com/joining-dropout-labs.html", "published_at": "2019-11-22T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de8467db850f", "title": "Let's Get Together: More Details on Me, You and My Dream Gig", "url": "https://blog.kjamistan.com/lets-get-together-more-details-on-me-you-and-my-dream-gig.html", "published_at": "2019-06-05T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de8468001c8b", "title": "Adversarial Learning for Good: My Talk at #34c3 on Deep Learning Blindspots", "url": "https://blog.kjamistan.com/adversarial-learning-for-good-my-talk-at-34c3-on-deep-learning-blindspots.html", "published_at": "2017-12-27T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846864d122", "title": "Towards Interpretable Reliable Models", "url": "https://blog.kjamistan.com/towards-interpretable-reliable-models.html", "published_at": "2017-10-28T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846885d00d", "title": "GDPR & You: My Talk at Cloudera Sessions München", "url": "https://blog.kjamistan.com/gdpr-you-my-talk-at-cloudera-sessions-munchen.html", "published_at": "2017-10-10T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de8468e36bf6", "title": "Algorithmic Art and \"Künstliche Kunst\"", "url": "https://blog.kjamistan.com/algorithmic-art-and-kunstliche-kunst.html", "published_at": "2017-10-06T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846961ed2f", "title": "Comparing scikit-learn Text Classifiers on a Fake News Dataset", "url": "https://blog.kjamistan.com/comparing-scikit-learn-text-classifiers-on-a-fake-news-dataset.html", "published_at": "2017-08-27T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de8469ba28d3", "title": "Data Unit Testing: EuroPython Tutorial", "url": "https://blog.kjamistan.com/data-unit-testing-europython-tutorial.html", "published_at": "2017-07-13T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846a285b27", "title": "if Ethics is not None", "url": "https://blog.kjamistan.com/if-ethics-is-not-none.html", "published_at": "2017-07-13T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846a37f750", "title": "Practical Data Cleaning with Python Resources", "url": "https://blog.kjamistan.com/practical-data-cleaning-with-python-resources.html", "published_at": "2017-05-02T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846a3b3895", "title": "PyData Amsterdam Keynote on Ethical Machine Learning", "url": "https://blog.kjamistan.com/pydata-amsterdam-keynote-on-ethical-machine-learning.html", "published_at": "2017-04-06T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846b2c9cac", "title": "Ten Tips for First-Time Conference Speakers", "url": "https://blog.kjamistan.com/ten-tips-for-first-time-conference-speakers.html", "published_at": "2017-02-10T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846b67bf30", "title": "The Practice of Programming: 18 Years Later", "url": "https://blog.kjamistan.com/the-practice-of-programming-18-years-later.html", "published_at": "2017-01-19T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846bedf8ca", "title": "New O'Reilly Video Training: Data Pipelines with Python", "url": "https://blog.kjamistan.com/new-oreilly-video-training-data-pipelines-with-python.html", "published_at": "2016-12-12T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846c4b44d0", "title": "DAGs & Dask: How and When to Accelerate your Data Analysis", "url": "https://blog.kjamistan.com/dags-dask-how-and-when-to-accelerate-your-data-analysis.html", "published_at": "2016-10-28T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846cd01786", "title": "Introduction to Data Wrangling @ PyConCZ", "url": "https://blog.kjamistan.com/introduction-to-data-wrangling-pyconcz.html", "published_at": "2016-10-28T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846cfc100d", "title": "Chatbot Scraper: Europarl Scraper: 24 Languages of Politics, at your fingertips", "url": "https://blog.kjamistan.com/chatbot-scraper-europarl-scraper-24-languages-of-politics-at-your-fingertips.html", "published_at": "2016-10-19T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846d0b92d3", "title": "Chatbot Scraper: Using (today's) IRC logs as your NLP datasets", "url": "https://blog.kjamistan.com/chatbot-scraper-using-todays-irc-logs-as-your-nlp-datasets.html", "published_at": "2016-09-28T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846d51f842", "title": "Automating your Data Cleanup with Python", "url": "https://blog.kjamistan.com/automating-your-data-cleanup-with-python.html", "published_at": "2016-09-16T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846e476cb3", "title": "Embedded *isms in Vector-Based Natural Language Processing", "url": "https://blog.kjamistan.com/embedded-isms-in-vector-based-natural-language-processing.html", "published_at": "2016-09-15T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846ef5b891", "title": "Obligatory Women In Tech Post", "url": "https://blog.kjamistan.com/obligatory-women-in-tech-post.html", "published_at": "2016-09-15T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de846fdcefa7", "title": "I Hate You, NLP ;)", "url": "https://blog.kjamistan.com/i-hate-you-nlp.html", "published_at": "2016-07-20T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de84702fb491", "title": "Python Flight Search", "url": "https://blog.kjamistan.com/python-flight-search.html", "published_at": "2016-03-28T22:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de8470d4c643", "title": "Data Wrangling with Python Course", "url": "https://blog.kjamistan.com/data-wrangling-with-python-course.html", "published_at": "2016-02-28T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de84714fb085", "title": "Data Wrangling with Python", "url": "https://blog.kjamistan.com/data-wrangling-with-python.html", "published_at": "2015-10-31T23:00:00+00:00" }, { "id": "01a0874d-2063-72ad-b57a-de8472333ca8", "title": "Europython 2015", "url": "https://blog.kjamistan.com/europython-2015.html", "published_at": "2015-07-22T22:00:00+00:00" } ] posts Claim your blog
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blog.kjamistan.com

2026

Privacy Evaluations for AI Systemsoriginal ↗
2 Sept 2026
Building an AI Privacy Routeroriginal ↗
12 Jul 2026
AI Guardrails Explainedoriginal ↗
17 Jun 2026
Using Synthetic Data for Privacy in AI/ML Systemsoriginal ↗
12 May 2026
Using Claude Code with Locally-Hosted modelsoriginal ↗
6 Apr 2026
Practical AI Privacy: A 6-week online Maven masterclassoriginal ↗
29 Mar 2026
Differential Privacy Parameters, Accounting and Auditing in Deep Learning and AIoriginal ↗
5 Feb 2026
Get your data local: Setting up Network Attached Storage (NAS) and your first steps in self-hostingoriginal ↗
30 Jan 2026
Building out my home AI Lab for private and local AIoriginal ↗
15 Jan 2026
Differential Privacy in Today's AI: What's so hard?original ↗
5 Jan 2026

2025

Differential Privacy in Deep Learningoriginal ↗
9 Nov 2025
Attacks on Machine Unlearning: How Unlearned Models Leak Informationoriginal ↗
12 Oct 2025
Machine Unlearning: How today's Unlearning is doneoriginal ↗
18 Sept 2025
Machine unlearning: what is it?original ↗
12 Aug 2025
AI Risk and Threat Taxonomiesoriginal ↗
4 Aug 2025
Algorithmic-based Guardrails: External guardrail models and alignment methodsoriginal ↗
27 Jul 2025
Blocking AI/ML Memorization with Software Guardrailsoriginal ↗
10 Jul 2025
Defining Privacy Attacks in AI and MLoriginal ↗
11 Jun 2025
Priveedly: your private and personal content reader and recommenderoriginal ↗
22 Jan 2025
Adversarial Examples Demonstrate Memorization Propertiesoriginal ↗
14 Jan 2025
Differential Privacy as a Counterexample to AI/ML Memorizationoriginal ↗
1 Jan 2025

2024

How Memorization Happens: Overparametrized Modelsoriginal ↗
17 Dec 2024
How memorization happens: Noveltyoriginal ↗
8 Dec 2024
How memorization happens: Repetitionoriginal ↗
2 Dec 2024
Gaming Evaluation - The evolution of deep learning training and evaluationoriginal ↗
25 Nov 2024
Exploring new meadowsoriginal ↗
19 Nov 2024
Private and Personalized AIoriginal ↗
18 Nov 2024
Encodings and embeddings: How does data get into machine learning systems?original ↗
17 Nov 2024
Machine Learning dataset distributions, history, and biasesoriginal ↗
12 Nov 2024
Deep learning memorization, and why you should careoriginal ↗
3 Nov 2024
A Deep Dive into Memorization in Deep Learningoriginal ↗
2 Nov 2024

2023

Building a Privacy-First Newsletteroriginal ↗
12 Mar 2023

2019

Joining Dropout Labs!original ↗
22 Nov 2019
Let's Get Together: More Details on Me, You and My Dream Gigoriginal ↗
5 Jun 2019

2017

Adversarial Learning for Good: My Talk at #34c3 on Deep Learning Blindspotsoriginal ↗
27 Dec 2017
Towards Interpretable Reliable Modelsoriginal ↗
28 Oct 2017
GDPR & You: My Talk at Cloudera Sessions Münchenoriginal ↗
10 Oct 2017
Algorithmic Art and "Künstliche Kunst"original ↗
6 Oct 2017
Comparing scikit-learn Text Classifiers on a Fake News Datasetoriginal ↗
27 Aug 2017
Data Unit Testing: EuroPython Tutorialoriginal ↗
13 Jul 2017
if Ethics is not Noneoriginal ↗
13 Jul 2017
Practical Data Cleaning with Python Resourcesoriginal ↗
2 May 2017
PyData Amsterdam Keynote on Ethical Machine Learningoriginal ↗
6 Apr 2017
Ten Tips for First-Time Conference Speakersoriginal ↗
10 Feb 2017
The Practice of Programming: 18 Years Lateroriginal ↗
19 Jan 2017

2016

New O'Reilly Video Training: Data Pipelines with Pythonoriginal ↗
12 Dec 2016
DAGs & Dask: How and When to Accelerate your Data Analysisoriginal ↗
28 Oct 2016
Introduction to Data Wrangling @ PyConCZoriginal ↗
28 Oct 2016
Chatbot Scraper: Europarl Scraper: 24 Languages of Politics, at your fingertipsoriginal ↗
19 Oct 2016
Chatbot Scraper: Using (today's) IRC logs as your NLP datasetsoriginal ↗
28 Sept 2016
Automating your Data Cleanup with Pythonoriginal ↗
16 Sept 2016
Embedded *isms in Vector-Based Natural Language Processingoriginal ↗
15 Sept 2016
Obligatory Women In Tech Postoriginal ↗
15 Sept 2016
I Hate You, NLP ;)original ↗
20 Jul 2016
Python Flight Searchoriginal ↗
28 Mar 2016
Data Wrangling with Python Courseoriginal ↗
28 Feb 2016

2015

Data Wrangling with Pythonoriginal ↗
31 Oct 2015
Europython 2015original ↗
22 Jul 2015