#kdai2026 — Public Fediverse posts

🎷 Session 03 of #KDAI2026 - Basic Machine Learning II went live today.
This week's transmission lands on 3 foundational algorithms:
🔭 k-Means Clustering — when there are no labels, let the data speak for itself
📉 Linear Regression — drawing the straightest line through the chaos
🌳 Decision Trees — asking the right questions in the right order.

Because every good lecture deserves a soundtrack. 🎶

#AI #MachineLearning #AIeducation #LehreKIT #CowboyBebop @fiz_karlsruhe @fizise

🎷 Session 03 of #KDAI2026 - Basic Machine Learning II went live today.
This week's transmission lands on 3 foundational algorithms:
🔭 k-Means Clustering — when there are no labels, let the data speak for itself
📉 Linear Regression — drawing the straightest line through the chaos
🌳 Decision Trees — asking the right questions in the right order.

Because every good lecture deserves a soundtrack. 🎶

#AI #MachineLearning #AIeducation #LehreKIT #CowboyBebop @fiz_karlsruhe @fizise

🎷 Session 03 of #KDAI2026 - Basic Machine Learning II went live today.
This week's transmission lands on 3 foundational algorithms:
🔭 k-Means Clustering — when there are no labels, let the data speak for itself
📉 Linear Regression — drawing the straightest line through the chaos
🌳 Decision Trees — asking the right questions in the right order.

Because every good lecture deserves a soundtrack. 🎶

#AI #MachineLearning #AIeducation #LehreKIT #CowboyBebop @fiz_karlsruhe @fizise

🎷 Session 03 of #KDAI2026 - Basic Machine Learning II went live today.
This week's transmission lands on 3 foundational algorithms:
🔭 k-Means Clustering — when there are no labels, let the data speak for itself
📉 Linear Regression — drawing the straightest line through the chaos
🌳 Decision Trees — asking the right questions in the right order.

Because every good lecture deserves a soundtrack. 🎶

#AI #MachineLearning #AIeducation #LehreKIT #CowboyBebop @fiz_karlsruhe @fizise

🎷 Session 03 of #KDAI2026 - Basic Machine Learning II went live today.
This week's transmission lands on 3 foundational algorithms:
🔭 k-Means Clustering — when there are no labels, let the data speak for itself
📉 Linear Regression — drawing the straightest line through the chaos
🌳 Decision Trees — asking the right questions in the right order.

Because every good lecture deserves a soundtrack. 🎶

#AI #MachineLearning #AIeducation #LehreKIT #CowboyBebop @fiz_karlsruhe @fizise

So, what did we learn in last week's lecture?
(1) The bounty log (history of AI)
(2) Symbolic vs subsymbolic (The two schools)
(3) The mechanics of the chase (ML types)
(4) The black box evaluation
Stay tuned for this weeks lecture on traditional ML technologies (k-Means, linear regression, decision trees)

#AI #machinelearning #cowboybebop #HistoryOfAI #modelEvaluation @fiz_karlsruhe @fizise #lecture #KDAI2026

So, what did we learn in last week's lecture?
(1) The bounty log (history of AI)
(2) Symbolic vs subsymbolic (The two schools)
(3) The mechanics of the chase (ML types)
(4) The black box evaluation
Stay tuned for this weeks lecture on traditional ML technologies (k-Means, linear regression, decision trees)

#AI #machinelearning #cowboybebop #HistoryOfAI #modelEvaluation @fiz_karlsruhe @fizise #lecture #KDAI2026

So, what did we learn in last week's lecture?
(1) The bounty log (history of AI)
(2) Symbolic vs subsymbolic (The two schools)
(3) The mechanics of the chase (ML types)
(4) The black box evaluation
Stay tuned for this weeks lecture on traditional ML technologies (k-Means, linear regression, decision trees)

#AI #machinelearning #cowboybebop #HistoryOfAI #modelEvaluation @fiz_karlsruhe @fizise #lecture #KDAI2026

So, what did we learn in last week's lecture?
(1) The bounty log (history of AI)
(2) Symbolic vs subsymbolic (The two schools)
(3) The mechanics of the chase (ML types)
(4) The black box evaluation
Stay tuned for this weeks lecture on traditional ML technologies (k-Means, linear regression, decision trees)

#AI #machinelearning #cowboybebop #HistoryOfAI #modelEvaluation @fiz_karlsruhe @fizise #lecture #KDAI2026

So, what did we learn in last week's lecture?
(1) The bounty log (history of AI)
(2) Symbolic vs subsymbolic (The two schools)
(3) The mechanics of the chase (ML types)
(4) The black box evaluation
Stay tuned for this weeks lecture on traditional ML technologies (k-Means, linear regression, decision trees)

#AI #machinelearning #cowboybebop #HistoryOfAI #modelEvaluation @fiz_karlsruhe @fizise #lecture #KDAI2026

Furthermore, we were discussing overfitting as another major problem with machine learning. SImply memorising the data doesn't help, when you have to make predictions over unknown data. When overfitting, the model looses the ability to generalise...

#AI #lecture #machine learning #KDAI2026 #overfitting #datascience #data @fiz_karlsruhe @fizise #knowledge

This week we were discussing the main challenges of Machine Learning in the #KDAI2026 lecture. It should be very obvious that "bad data quality leads to bad results" :)
However, we were also talking about insufficient number of data, non-representative data, irrelevant features, overfitting and various forms of bias.

@fiz_karlsruhe #AI #machinelearning #unicorn #dataquality #lecture #datascience

After today's #KDAI2026 lecture on "Basic Machine Learning 01", you will understand why most of what people say about AI in public debate is either wrong, confused, or missing the point — and you will have the tools to do better. If you've ever wondered how Netflix predicts your next binge-watch or how self-driving cars navigate, this is where it all starts.

@fizise #AI #machinelearning #DeepLearning #transformers #llms #ontologies #historyofAI #lecture #StudentLife #FutureTech #STEM

We renamed the Information Service Engineering lecture into "Knowledge-driven AI", simply because what we teach is knowledge-driven AI :) which pertains knowledge representation, natural language processing, machine learning, and reasoning. We adapted the focus emphasizing the machine learning part by going deeper into deep learning, transformer architectures, and large language models.

#KDAI2026 #lecture @fizise @fiz_karlsruhe #AI #knowledgerepresentation #knowledgegraphs #machinelearning #nlp

We renamed the Information Service Engineering lecture into "Knowledge-driven AI", simply because what we teach is knowledge-driven AI :) which pertains knowledge representation, natural language processing, machine learning, and reasoning. We adapted the focus emphasizing the machine learning part by going deeper into deep learning, transformer architectures, and large language models.

#KDAI2026 #lecture @fizise @fiz_karlsruhe #AI #knowledgerepresentation #knowledgegraphs #machinelearning #nlp

We renamed the Information Service Engineering lecture into "Knowledge-driven AI", simply because what we teach is knowledge-driven AI :) which pertains knowledge representation, natural language processing, machine learning, and reasoning. We adapted the focus emphasizing the machine learning part by going deeper into deep learning, transformer architectures, and large language models.

#KDAI2026 #lecture @fizise @fiz_karlsruhe #AI #knowledgerepresentation #knowledgegraphs #machinelearning #nlp

We renamed the Information Service Engineering lecture into "Knowledge-driven AI", simply because what we teach is knowledge-driven AI :) which pertains knowledge representation, natural language processing, machine learning, and reasoning. We adapted the focus emphasizing the machine learning part by going deeper into deep learning, transformer architectures, and large language models.

#KDAI2026 #lecture @fizise @fiz_karlsruhe #AI #knowledgerepresentation #knowledgegraphs #machinelearning #nlp

We renamed the Information Service Engineering lecture into "Knowledge-driven AI", simply because what we teach is knowledge-driven AI :) which pertains knowledge representation, natural language processing, machine learning, and reasoning. We adapted the focus emphasizing the machine learning part by going deeper into deep learning, transformer architectures, and large language models.

#KDAI2026 #lecture @fizise @fiz_karlsruhe #AI #knowledgerepresentation #knowledgegraphs #machinelearning #nlp

🔍 Lecture 01 — The Art of Understanding
Before we teach machines to reason, we should ask ourselves: what is knowledge, really?
This opening lecture steps back from the algorithms and starts with first principles.
It's the philosophical foundation the rest of the course is built on. Bring your curiosity. Leave your assumptions at the door.
#KDAI2026 #AI #Epistemology #DataToKnowledge #SemanticWeb #KnowledgeRepresentation #MachineLearning #PhilosophyOfAI @fizise @fiz_karlsruhe

🔍 Lecture 01 — The Art of Understanding
Before we teach machines to reason, we should ask ourselves: what is knowledge, really?
This opening lecture steps back from the algorithms and starts with first principles.
It's the philosophical foundation the rest of the course is built on. Bring your curiosity. Leave your assumptions at the door.
#KDAI2026 #AI #Epistemology #DataToKnowledge #SemanticWeb #KnowledgeRepresentation #MachineLearning #PhilosophyOfAI @fizise @fiz_karlsruhe

🔍 Lecture 01 — The Art of Understanding
Before we teach machines to reason, we should ask ourselves: what is knowledge, really?
This opening lecture steps back from the algorithms and starts with first principles.
It's the philosophical foundation the rest of the course is built on. Bring your curiosity. Leave your assumptions at the door.
#KDAI2026 #AI #Epistemology #DataToKnowledge #SemanticWeb #KnowledgeRepresentation #MachineLearning #PhilosophyOfAI @fizise @fiz_karlsruhe

🔍 Lecture 01 — The Art of Understanding
Before we teach machines to reason, we should ask ourselves: what is knowledge, really?
This opening lecture steps back from the algorithms and starts with first principles.
It's the philosophical foundation the rest of the course is built on. Bring your curiosity. Leave your assumptions at the door.
#KDAI2026 #AI #Epistemology #DataToKnowledge #SemanticWeb #KnowledgeRepresentation #MachineLearning #PhilosophyOfAI @fizise @fiz_karlsruhe

🔍 Lecture 01 — The Art of Understanding
Before we teach machines to reason, we should ask ourselves: what is knowledge, really?
This opening lecture steps back from the algorithms and starts with first principles.
It's the philosophical foundation the rest of the course is built on. Bring your curiosity. Leave your assumptions at the door.
#KDAI2026 #AI #Epistemology #DataToKnowledge #SemanticWeb #KnowledgeRepresentation #MachineLearning #PhilosophyOfAI @fizise @fiz_karlsruhe

🎓 Knowledge-driven AI is back — Summer Semester 2026.
12 lectures. One central question: What does it actually mean for a machine to understand?
We'll journey from Aristotle's categories to knowledge graphs, from the first perceptron to today's foundation models — exploring how symbolic reasoning and modern machine learning meet, clash, and complement each other.

#KDAI2026 #AI #MachineLearning #KnowledgeGraphs #SemanticWeb @fizise @KIT_Karlsruhe @fiz_karlsruhe #HigherEducation #AILiteracy