We know that creating knowledge graphs from unstructured data can be a headache. Now? The Neo4j GraphRAG for Python package includes a Knowledge Graph Builder to help you convert your unstructured and structured data. The result: Organized representations of real-world entities and relationships that power better #AI applications. Read more about this ⬆️ in the blog and learn how to create them in the #GraphAcademy course "Constructing Knowledge Graphs with Neo4j GraphRAG for Python." https://bit.ly/4pRh6iK #Python #Neo4j
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We know that creating knowledge graphs from unstructured data can be a headache. Now? The Neo4j GraphRAG for Python package includes a Knowledge Graph Builder to help you convert your unstructured and structured data. The result: Organized representations of real-world entities and relationships that power better #AI applications. Read more about this ⬆️ in the blog and learn how to create them in the #GraphAcademy course "Constructing Knowledge Graphs with Neo4j GraphRAG for Python." https://bit.ly/4pRh6iK #Python #Neo4j
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We know that creating knowledge graphs from unstructured data can be a headache. Now? The Neo4j GraphRAG for Python package includes a Knowledge Graph Builder to help you convert your unstructured and structured data. The result: Organized representations of real-world entities and relationships that power better #AI applications. Read more about this ⬆️ in the blog and learn how to create them in the #GraphAcademy course "Constructing Knowledge Graphs with Neo4j GraphRAG for Python." https://bit.ly/4pRh6iK #Python #Neo4j
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Hello Python folks Quick brain-teaser for you: What does this print — and why? t = ([1, 2],) t[0] += [3] print(t) Did the tuple mutate? Or did Python just trick your mental model? Most people answer quickly. Very few explain it correctly. If you can explain this in terms of identity, mutation vs rebinding, you truly understand Python. Full breakdown here including👇 - Shallow Vs Deep Copy - Default Mutable Argument Trap https://lnkd.in/e_v6nNej #python #pythoninterview #softwaredevelopment
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Cluster-Based QML Inference. Goal-oriented agents managing real-time prediction fixes on federated multi-QPU edge nodes. Skills: Python, scikit-learn. https://lnkd.in/dR837zSA #Branch51 #EdgeAI #QuantumInference
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Python you actually need for GenAI You don’t need to learn all of Python to work with GenAI. Most GenAI systems rely on a small set of Python patterns: control flow, state, and orchestration. The mistake many people make is trying to “finish Python” before understanding how GenAI systems behave. Learn Python to steer systems — not to master the language. #GenAI #Python #AIAgents #AIEngineering #ArtificialIntelligence
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Recursion Finally Clicked in Python A function calling itself sounded scary… until it made sense. 🔁 Big problem → break into smaller ones 🛑 Base case → where it stops 📌 Example: factorial(n) calling factorial(n-1) Think Russian nesting dolls, keep opening until the smallest one. 💡 Lesson: Recursion isn’t always needed, but when it fits, it’s elegant. Learning Python beyond loops #Python #Recursion #LearningInPublic #CodingJourney #Coursera
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Many people think Python is about writing models. In GenAI systems, Python plays a different role. It controls: • decision flow • tool orchestration • state and memory • how models are actually used That’s why you don’t need to master all of Python before starting with GenAI. You need enough Python to steer the system — not to build the model itself. #GenAI #Python #AIAgents #AIEngineering #ArtificialIntelligence
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Understanding Strings & Immutability As I continue building my Python fundamentals, I have been learning how strings work and why they are immutable in Python. - Strings are sequences of characters enclosed in single or double quotes both work the same in Python. - Learned how to create multi-line strings, handle quotes inside strings, and check for characters using the in operator. - Explored string length using len() and accessed characters through indexing (including negative indexing). - An important concept: strings are immutable, meaning individual characters cannot be changed once a string is created only reassigned. Understanding string behaviour is essential when cleaning, validating, and analyzing text-based data. #PythonBasics #StringsInPython #Immutability #DataAnalyticsJourney #LearningInPublic #Upskilling
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Strings in Python are sequences of characters used to store and work with text. They support indexing, slicing, concatenation, repetition, and many useful methods. An important concept to remember: Strings are immutable — once created, their characters cannot be changed directly. Any modification creates a new string. #Python #StringsInPython #ProgrammingBasics
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