Fix TDS links (#20)

Author: tomasonjo

src/content/docs/concepts/intro-to-graphrag.md

@@ -115,5 +115,5 @@ In the above example, a vector similarity search is executed on the existing ind
 ## Further Reading
 
 * [Neo4j GraphAcademy: Build a Neo4j-backed Chatbot using Python](https://graphacademy.neo4j.com/courses/llm-chatbot-python/) 
-* [Integrating Neo4j into the LangChain ecosystem](https://towardsdatascience.com/integrating-neo4j-into-the-langchain-ecosystem-df0e988344d2)
+* [Integrating Neo4j into the LangChain ecosystem](https://medium.com/data-science/integrating-neo4j-into-the-langchain-ecosystem-df0e988344d2)
 * [Neo4j GraphAcademy: Mastering Retrieval-Augmented Generation (RAG)](https://graphacademy.neo4j.com/courses/genai-workshop-graphrag/)

src/content/docs/reference/graphrag/cypher-templates.md

@@ -31,7 +31,7 @@ Several domain-specific Cypher queries (containing parameters) and a description
 
 ## Further reading
 
-- [Enhancing Interaction between Language Models and Graph Databases via a Semantic Layer](https://towardsdatascience.com/enhancing-interaction-between-language-models-and-graph-databases-via-a-semantic-layer-0a78ad3eba49) (January 2024)
+- [Enhancing Interaction between Language Models and Graph Databases via a Semantic Layer](https://medium.com/data-science/enhancing-interaction-between-language-models-and-graph-databases-via-a-semantic-layer-0a78ad3eba49) (January 2024)
 
 ## Existing Implementations
 

src/content/docs/reference/graphrag/global-community-summary-retriever.md

@@ -61,7 +61,7 @@ There are several variations in which you could use the Lexical Graph with extra
 
 - [From Local to Global:A Graph RAG Approach to Query-Focused Summarization](https://arxiv.org/pdf/2404.16130) (April 2024)
 - [Implementing 'From Local to Global' GraphRAG with Neo4j and LangChain: Constructing the Graph](https://neo4j.com/developer-blog/global-graphrag-neo4j-langchain/) (July 2024)
-- [Integrating Microsoft GraphRAG into Neo4j](https://towardsdatascience.com/integrating-microsoft-graphrag-into-neo4j-e0d4fa00714c) (July 2024)
+- [Integrating Microsoft GraphRAG into Neo4j](https://medium.com/data-science/integrating-microsoft-graphrag-into-neo4j-e0d4fa00714c) (July 2024)
 - [Introducing DRIFT Search: Combining global and local search methods to improve quality and efficiency - Microsoft Research](https://www.microsoft.com/en-us/research/blog/introducing-drift-search-combining-global-and-local-search-methods-to-improve-quality-and-efficiency/)
 
 ## Existing Implementations

src/content/docs/reference/graphrag/text2cypher.md

@@ -113,7 +113,7 @@ from [Benchmarking Using the Neo4j Text2Cypher (2024) Dataset](https://neo4j.com
 
 ## Existing Implementations
 
-- [Integrating Neo4j into the LangChain ecosystem](https://towardsdatascience.com/integrating-neo4j-into-the-langchain-ecosystem-df0e988344d2) (Tomaz Bratanic, April 2024)
+- [Integrating Neo4j into the LangChain ecosystem](https://medium.com/data-science/integrating-neo4j-into-the-langchain-ecosystem-df0e988344d2) (Tomaz Bratanic, April 2024)
 - [LangChain Cypher Search: Tips & Tricks](https://neo4j.com/developer-blog/langchain-cypher-search-tips-tricks/) (Tomaz Bratanic, June 2024)
 
 - [Langchain: GraphCypherQAChain](https://python.langchain.com/v0.2/docs/integrations/providers/neo4j/#graphcypherqachain)