Fixed: Markdown tables incorrectly given text code fences.

04-prompt-engineering-fundamentals/README.md

@@ -224,11 +224,9 @@ In the above examples, the prompt was still fairly open-ended, allowing the LLM
 
 Here's an example where the instruction is to "summarize this in 2 sentences".
 
-```text
 | Prompt (Input) | Completion (Output) |
 |:---|:---|
 | Jupiter is the fifth planet from the Sun and the largest in the Solar System. It is a gas giant with a mass one-thousandth that of the Sun, but two-and-a-half times that of all the other planets in the Solar System combined. Jupiter is one of the brightest objects visible to the naked eye in the night sky, and has been known to ancient civilizations since before recorded history. It is named after the Roman god Jupiter.[19] When viewed from Earth, Jupiter can be bright enough for its reflected light to cast visible shadows,[20] and is on average the third-brightest natural object in the night sky after the Moon and Venus. <br/> **Summarize this in 2 short sentences** | Jupiter, the fifth planet from the Sun, is the largest in the Solar System and is known for being one of the brightest objects in the night sky. Named after the Roman god Jupiter, it's a gas giant whose mass is two-and-a-half times that of all other planets in the Solar System combined. |
-```
 
 The primary content segment can be used in various ways to drive more effective instructions:
 
@@ -248,29 +246,29 @@ The prompt now consists of three components:
 - A few examples of the desired output
 - The start of a new example (which becomes an implicit task description)
 
-    ```text
-    | Learning Type | Prompt (Input) | Completion (Output) |
-    |:---|:---|:---|
-    | Zero-shot  | "The Sun is Shining". Translate to Spanish  | "El Sol está brillando".|
-    | One-shot | "The Sun is Shining" => ""El Sol está brillando". <br> "It's a Cold and Windy Day" => | "Es un día frío y ventoso". |
-    | Few-shot | The player ran the bases => Baseball  <br/> The player hit an ace => Tennis  <br/> The player hit a six => Cricket  <br/> The player made a slam-dunk => | Basketball |
-    | | | |
-    ```
+
+| Learning Type | Prompt (Input) | Completion (Output) |
+|:---|:---|:---|
+| Zero-shot  | "The Sun is Shining". Translate to Spanish  | "El Sol está brillando".|
+| One-shot | "The Sun is Shining" => ""El Sol está brillando". <br> "It's a Cold and Windy Day" => | "Es un día frío y ventoso". |
+| Few-shot | The player ran the bases => Baseball  <br/> The player hit an ace => Tennis  <br/> The player hit a six => Cricket  <br/> The player made a slam-dunk => | Basketball |
+| | | |
+
 
 Note how we had to provide explicit instruction ("Translate to Spanish") in zero-shot prompting, but it gets inferred in the one-shot prompting example. The few-shot example shows how adding more examples allows models to make more accurate inferences with no added instructions.
 
 ### Prompt Cues
 
 Another technique for using primary content is to provide _cues_ rather than examples. In this case, we are giving the model a nudge in the right direction by _starting it off_ with a snippet that reflects the desired response format. The model then "takes the cue" to continue in that vein.
 
-```text
+
 | Number of Cues | Prompt (Input) | Completion (Output) |
 |:---|:---|:---|
 | 0  | Jupiter is the fifth planet from the Sun and the largest in the Solar System. It is a gas giant with a mass one-thousandth that of the Sun, but two-and-a-half times that of all the other planets in the Solar System combined. Jupiter is one of the brightest objects visible to the naked eye in the night sky, and has been known to ancient civilizations since before recorded history.  <br/>**Summarize This**  | Jupiter is the largest planet in our Solar System and the fifth one from the Sun. It is a gas giant with a mass 1/1000th of the Sun's, but it is heavier than all the other planets combined. Ancient civilizations have known about Jupiter for a long time, and it is easily visible in the night sky..|
 | 1 | Jupiter is the fifth planet from the Sun and the largest in the Solar System. It is a gas giant with a mass one-thousandth that of the Sun, but two-and-a-half times that of all the other planets in the Solar System combined. Jupiter is one of the brightest objects visible to the naked eye in the night sky, and has been known to ancient civilizations since before recorded history.  <br/>**Summarize This** <br/> What we learned is that Jupiter | is the fifth planet from the Sun and the largest in the Solar System. It is a gas giant with a mass one-thousandth that of the Sun, but two-and-a-half times that of all the other planets combined. It is easily visible to the naked eye and has been known since ancient times. |
 | 2 | Jupiter is the fifth planet from the Sun and the largest in the Solar System. It is a gas giant with a mass one-thousandth that of the Sun, but two-and-a-half times that of all the other planets in the Solar System combined. Jupiter is one of the brightest objects visible to the naked eye in the night sky, and has been known to ancient civilizations since before recorded history.  <br/>**Summarize This** <br/> Top 3 Facts We Learned: | 1. Jupiter is the fifth planet from the Sun and the largest in the Solar System. <br/> 2. It is a gas giant with a mass one-thousandth that of the Sun...<br/> 3. Jupiter has been visible to the naked eye since ancient times ... |
 | | | |
-```
+
 
 ### Prompt Templates
 
@@ -323,7 +321,6 @@ Prompt Engineering is a trial-and-error process so keep three broad guiding fact
 
 Now let's look at common best practices that are recommended by [Open AI](https://help.openai.com/en/articles/6654000-best-practices-for-prompt-engineering-with-openai-api) and [Azure OpenAI](https://learn.microsoft.com/azure/ai-services/openai/concepts/prompt-engineering#best-practices?WT.mc_id=academic-105485-koreyst) practitioners.
 
-```text
 | What | Why |
 |:---|:---|
 | Evaluate the latest models. | New model generations are likely to have improved features and quality - but may also incur higher costs. Evaluate them for impact, then make migration decisions. |
@@ -335,7 +332,6 @@ Now let's look at common best practices that are recommended by [Open AI](https:
 | Order Matters | The order in which you present information to the model may impact the output, even in the learning examples, thanks to recency bias. Try different options to see what works best.|
 |Give the model an “out” | Give the model a _fallback_ completion response it can provide if it cannot complete the task for any reason. This can reduce chances of models generating false or hallucinatory responses. |
 | | |
-```
 
 As with any best practice, remember that _your mileage may vary_ based on the model, the task and the domain. Use these as a starting point, and iterate to find what works best for you. Constantly re-evaluate your prompt engineering process as new models and tools become available, with a focus on process scalability and response quality.