Repository of the final project for Le Wagon's Data Science course! This project was developed to showcase the skills acquired throughout the course, with a special focus on Generative AI.
Be clear and specific about what you want the AI to do. Ambiguities can lead to incorrect or irrelevant outputs.
2️⃣ Contextual Information: MAYBE FEW SHOT PROMPTING
Provide sufficient background information when necessary. Context helps the AI generate more relevant and precise responses.
3️⃣Moderation and Safety:
Implement content filters and moderation to prevent the generation of inappropriate, harmful, or biased content. This includes filtering out hate speech, explicit content, and ensuring compliance with legal and ethical standards.
4️⃣ Error Handling:
Prepare for and handle errors or misunderstandings in AI responses. This might involve clarifying questions from the AI or fallback strategies when the AI is unsure.
5️⃣ Bias Detection and Mitigation:
Be aware of and actively work to mitigate biases in AI responses, which can stem from biased training data or skewed algorithms.
6️⃣ Feedback Mechanisms:
Allow users to provide feedback on AI responses. This helps in refining and improving the AI model continuously.
1️⃣ Clarity and Specificity:
2️⃣ Contextual Information: MAYBE FEW SHOT PROMPTING
3️⃣Moderation and Safety:
4️⃣ Error Handling:
5️⃣ Bias Detection and Mitigation:
6️⃣ Feedback Mechanisms: