Remove promotional content from office hours and talks sections

Author: jxnl

docs/office-hours/cohort2/week1-summary.md

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-If you want to learn more about RAG systems, check out our RAG Playbook course. Here is a 20% discount code for readers.
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-[RAG Playbook - 20% off for readers](https://maven.com/applied-llms/rag-playbook?promoCode=EBOOK){ .md-button }
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 ## What is your take on DSpy? Should we use it?
 
 Generally, I think DSpy allows you to do some kind of prompt optimization by synthetically creating a bunch of few-shot examples and then identifying which of these examples could improve the performance of your system.

docs/office-hours/cohort2/week2-summary.md

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-If you want to learn more about RAG systems, check out our RAG Playbook course. Here is a 20% discount code for readers.
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-[RAG Playbook - 20% off for readers](https://maven.com/applied-llms/rag-playbook?promoCode=EBOOK){ .md-button }
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 ## How would you evaluate the effect of different parsing strategies in RAG, notably on documents with weird layouts, tables, and charts?
 
 For documents with complex layouts like tables and charts, there are multiple levels of evaluation:

docs/office-hours/cohort2/week3-summary.md

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-If you want to learn more about RAG systems, check out our RAG Playbook course. Here is a 20% discount code for readers.
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-[RAG Playbook - 20% off for readers](https://maven.com/applied-llms/rag-playbook?promoCode=EBOOK){ .md-button }
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 ## When gathering negative feedback from documents not being found, how do we use and validate the reliability of an LLM labeler?
 
 When it comes to getting negative feedback that documents were not found, I'd assume we're running into issues around low recall. This might manifest as low re-ranker scores or low cosine similarities with embedding models.

docs/office-hours/cohort2/week4-summary.md

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-If you want to learn more about RAG systems, check out our RAG Playbook course. Here is a 20% discount code for readers.
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-[RAG Playbook - 20% off for readers](https://maven.com/applied-llms/rag-playbook?promoCode=EBOOK){ .md-button }
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 ## What can "segments" mean beyond query volume and satisfaction values in a RAG system?
 
 Segmentation really depends on who your customers are and what they're trying to do. With a generic chatbot, it's hard to figure out what segmentation means. But if you think about intents of a specific application, you can uncover different patterns.

docs/office-hours/cohort2/week5-summary.md

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-If you want to learn more about RAG systems, check out our RAG Playbook course. Here is a 20% discount code for readers.
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-[RAG Playbook - 20% off for readers](https://maven.com/applied-llms/rag-playbook?promoCode=EBOOK){ .md-button }
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 ## How should we handle Excel files with multiple sheets and tables?
 
 Handling Excel files with multiple sheets and tables is challenging, and few companies have solved this problem well. Experience from companies like Zapier shows that connecting Excel spreadsheets to automation tools requires many controls to work properly.

docs/office-hours/cohort2/week6-summary.md

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-If you want to learn more about RAG systems, check out our RAG Playbook course. Here is a 20% discount code for readers.
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-[RAG Playbook - 20% off for readers](https://maven.com/applied-llms/rag-playbook?promoCode=EBOOK){ .md-button }
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 ## What is Deep Research and how does it relate to RAG?
 
 Deep Research is essentially a model fine-tuned for tool use that leverages RAG and iteration in a loop to produce reports. It can be viewed as RAG with solid data sources and strong reasoning capabilities on top. Deep Research is distinct from standard RAG applications because it typically produces more comprehensive outputs like reports rather than just answering specific questions.

docs/office-hours/cohort3/week-1-1.md

@@ -23,10 +23,6 @@ I hosted an office hours session focused on RAG implementation challenges, preci
 
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-If you want to learn more about RAG systems, check out our RAG Playbook course. Here is a 20% discount code for readers.
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-[RAG Playbook - 20% off for readers](https://maven.com/applied-llms/rag-playbook?promoCode=EBOOK){ .md-button }
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 ## How should we understand precision in the context of LLMs and RAG?

docs/office-hours/cohort3/week-1-2.md

@@ -24,10 +24,6 @@ I hosted an office hours session focused on RAG implementation challenges, preci
 
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-If you want to learn more about RAG systems, check out our RAG Playbook course. Here is a 20% discount code for readers.
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-[RAG Playbook - 20% off for readers](https://maven.com/applied-llms/rag-playbook?promoCode=EBOOK){ .md-button }
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 ## How should we understand precision in the context of LLMs and RAG?

docs/office-hours/cohort3/week-2-1.md

@@ -26,10 +26,6 @@ I hosted an office hours session focused on advanced retrieval-augmented generat
 
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-If you want to learn more about RAG systems, check out our RAG Playbook course. Here is a 20% discount code for readers.
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-[RAG Playbook - 20% off for readers](https://maven.com/applied-llms/rag-playbook?promoCode=EBOOK){ .md-button }
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 ## How should I approach medical RAG systems with complex queries?

docs/office-hours/cohort3/week-2-2.md

@@ -27,10 +27,6 @@ I hosted an office hours session focused on retrieval-augmented generation (RAG)
 
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-If you want to learn more about RAG systems, check out our RAG Playbook course. Here is a 20% discount code for readers.
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-[RAG Playbook - 20% off for readers](https://maven.com/applied-llms/rag-playbook?promoCode=EBOOK){ .md-button }
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 ## How can I apply course concepts to my actual project while balancing time constraints?