Update Sample Dialogs authored by Asif Khan's avatar Asif Khan
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#### Dialog 1: Seeking Romance Recommendations #### Dialog 1: Seeking Romance Recommendations
User: Hi there! **User**: Hi there!
Chatbot: Hello and welcome! I’m here to help predict the genre of any movie you’re interested in and provide recommendations. How can I assist you today? **Chatbot:** Hello and welcome! I’m here to help predict the genre of any movie you’re interested in and provide recommendations. How can I assist you today?
User: I’m in the mood for a romantic movie. Can you suggest some good ones? **User**: I’m in the mood for a romantic movie. Can you suggest some good ones?
Chatbot: Absolutely! Here are a few popular romantic movies currently trending on Netflix: **Chatbot:** Absolutely! Here are a few popular romantic movies currently trending on Netflix:
1. To All the Boys I’ve Loved Before **1.** To All the Boys I’ve Loved Before
2. Set It Up **2.** Set It Up
3. The Kissing Booth **3.** The Kissing Booth
User: Could you give me a brief summary of each? **User:** Could you give me a brief summary of each?
Chatbot: **Chatbot:**
1. To All the Boys I’ve Loved Before: A high school romance that begins when hidden love letters get mailed out to all of the main character’s crushes. **1.** To All the Boys I’ve Loved Before: A high school romance that begins when hidden love letters get mailed out to all of the main character’s crushes.
2. Set It Up: Two overworked assistants team up to set up their demanding bosses in the hope of alleviating their hectic work lives. **2.** Set It Up: Two overworked assistants team up to set up their demanding bosses in the hope of alleviating their hectic work lives.
3. The Kissing Booth: A teenage girl’s first love is complicated by her friendship with the boy’s brother. **3.** The Kissing Booth: A teenage girl’s first love is complicated by her friendship with the boy’s brother.
User: Nice! I think I’ll start with To All the Boys I’ve Loved Before. Thank you! **User:** Nice! I think I’ll start with To All the Boys I’ve Loved Before. Thank you!
Chatbot: You’re welcome! Enjoy the movie, and let me know if you’d like any more recommendations. **Chatbot:** You’re welcome! Enjoy the movie, and let me know if you’d like any more recommendations.
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#### Dialog 2: Family-Friendly Action Flicks #### Dialog 2: Family-Friendly Action Flicks
User: Hello! **User:** Hello!
Chatbot: Hi there! I can help you find movies, predict genres, or explore any film data you need. What can I assist you with today? **Chatbot:** Hi there! I can help you find movies, predict genres, or explore any film data you need. What can I assist you with today?
User: I’m looking for a family-friendly action movie for a weekend watch party. Any suggestions? **User:** I’m looking for a family-friendly action movie for a weekend watch party. Any suggestions?
Chatbot: Sure! Here are some action movies suitable for most ages: **Chatbot:** Sure! Here are some action movies suitable for most ages:
1. Spy Kids **1.** Spy Kids
2. The Adventures of Sharkboy and Lavagirl **2.** The Adventures of Sharkboy and Lavagirl
3. We Can Be Heroes **3.** We Can Be Heroes
User: Which one is the most popular? **User:** Which one is the most popular?
Chatbot: Spy Kids has been consistently popular for family audiences due to its fun spy gadget theme and comedic moments. **Chatbot:** Spy Kids has been consistently popular for family audiences due to its fun spy gadget theme and comedic moments.
User: Great, I’ll check out Spy Kids. Thanks! **User:** Great, I’ll check out Spy Kids. Thanks!
Chatbot: You’re welcome! Feel free to come back if you’d like more recommendations. **Chatbot:** You’re welcome! Feel free to come back if you’d like more recommendations.
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...@@ -57,43 +57,43 @@ Chatbot: You’re welcome! Feel free to come back if you’d like more recommend ...@@ -57,43 +57,43 @@ Chatbot: You’re welcome! Feel free to come back if you’d like more recommend
#### Dialog 1: Delving Into Viewer Demographics #### Dialog 1: Delving Into Viewer Demographics
User: Hi. **User:** Hi.
Chatbot: Hello and welcome! I can assist you with exploring movie genre predictions, data insights, or any analysis you need on the Netflix dataset. How can I help you today? **Chatbot:** Hello and welcome! I can assist you with exploring movie genre predictions, data insights, or any analysis you need on the Netflix dataset. How can I help you today?
User: I’d like to know about viewer demographics for comedy movies. Any insights? **User:** I’d like to know about viewer demographics for comedy movies. Any insights?
Chatbot: Sure! According to our data: **Chatbot:** Sure! According to our data:
- Comedy films have the highest viewership among the 18-34 age group. - Comedy films have the highest viewership among the 18-34 age group.
- Peak streaming times are usually weekends between 6 PM and 9 PM. - Peak streaming times are usually weekends between 6 PM and 9 PM.
User: How about drama? Do they also appeal to the same demographic? **User:** How about drama? Do they also appeal to the same demographic?
Chatbot: Dramas show a broader appeal, typically watched by a 25-45 age range, with viewership spikes on weekday evenings. **Chatbot:** Dramas show a broader appeal, typically watched by a 25-45 age range, with viewership spikes on weekday evenings.
User: This is great info. Thank you! **User:** This is great info. Thank you!
Chatbot: Glad to help! Let me know if you need any more strategic insights. **Chatbot:** Glad to help! Let me know if you need any more strategic insights.
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#### Dialog 2: Comparing Seasonal Trends #### Dialog 2: Comparing Seasonal Trends
User: Hi again! **User:** Hi again!
Chatbot: Hello! Ready for more data-driven insights on Netflix trends? **Chatbot:** Hello! Ready for more data-driven insights on Netflix trends?
User: Yes. I want to compare viewership trends for different genres across seasons. Can you help? **User:** Yes. I want to compare viewership trends for different genres across seasons. Can you help?
Chatbot: During winter, drama and romance do well (holiday seasons). In summer, action and comedy spike due to family gatherings and free time.. **Chatbot:** During winter, drama and romance do well (holiday seasons). In summer, action and comedy spike due to family gatherings and free time..
User: Interesting. Any specific months that stand out? **User:** Interesting. Any specific months that stand out?
Chatbot: December and January show notably high drama viewership, while June and July see a surge in action/comedy streaming. **Chatbot:** December and January show notably high drama viewership, while June and July see a surge in action/comedy streaming.
User: That’s very useful. Thanks! **User:** That’s very useful. Thanks!
Chatbot: You’re most welcome! I’m here if you need more insights for your content strategy. **Chatbot:** You’re most welcome! I’m here if you need more insights for your content strategy.
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...@@ -102,46 +102,46 @@ Chatbot: You’re most welcome! I’m here if you need more insights for your co ...@@ -102,46 +102,46 @@ Chatbot: You’re most welcome! I’m here if you need more insights for your co
#### Dialog 1: Model Evaluation Metrics #### Dialog 1: Model Evaluation Metrics
User: Hello. **User:** Hello.
Chatbot: Hi there! I can explain our data preprocessing steps, show you model metrics, or help with any other data-related insights you might need. What are you interested in today? **Chatbot:** Hi there! I can explain our data preprocessing steps, show you model metrics, or help with any other data-related insights you might need. What are you interested in today?
User: Can you tell me about how you evaluate your genre prediction model? **User:** Can you tell me about how you evaluate your genre prediction model?
Chatbot: Absolutely! We use several metrics: **Chatbot:** Absolutely! We use several metrics:
1. Accuracy: Gives the percentage of correctly predicted genres. **1.** Accuracy: Gives the percentage of correctly predicted genres.
2. F1-Score: Balances precision and recall, especially useful if some genres have fewer movies. **2.** F1-Score: Balances precision and recall, especially useful if some genres have fewer movies.
3. ROC-AUC: Measures how well the model distinguishes between genres. **3.** ROC-AUC: Measures how well the model distinguishes between genres.
User: Can you share the latest accuracy figure? **User:** Can you share the latest accuracy figure?
Chatbot: Our current genre classification model is at about 85% accuracy across 5 major genres. **Chatbot:** Our current genre classification model is at about 85% accuracy across 5 major genres.
User: That’s impressive. Thank you! **User:** That’s impressive. Thank you!
Chatbot: You’re welcome! Let me know if you need additional model details. **Chatbot:** You’re welcome! Let me know if you need additional model details.
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#### Dialog 2: Feature Engineering Approaches #### Dialog 2: Feature Engineering Approaches
User: Hello again. **User:** Hello again.
Chatbot: Welcome back! How can I help with your data science queries today? **Chatbot:** Welcome back! How can I help with your data science queries today?
User: I’m curious about how you engineer new features from the raw data. Any examples? **User:** I’m curious about how you engineer new features from the raw data. Any examples?
Chatbot: Sure! Here are a few: **Chatbot:** Sure! Here are a few:
1. Director Frequency: We count how often a director appears in the dataset to capture their popularity. **1.** Director Frequency: We count how often a director appears in the dataset to capture their popularity.
2. Seasonal Release: We categorize launch dates into seasons (e.g., winter, summer) to see if release timing influences genre. **2.** Seasonal Release: We categorize launch dates into seasons (e.g., winter, summer) to see if release timing influences genre.
3. Title Keyword Extraction: We perform basic NLP to identify key words in titles that might hint at genres. **3.** Title Keyword Extraction: We perform basic NLP to identify key words in titles that might hint at genres.
User: That’s great. Do you also use one-hot encoding for any categorical data? **User:** That’s great. Do you also use one-hot encoding for any categorical data?
Chatbot: Yes, for columns like country and language, we apply one-hot encoding to convert them into numerical form for the model. **Chatbot:** Yes, for columns like country and language, we apply one-hot encoding to convert them into numerical form for the model.
User: Perfect. Thanks so much! **User:** Perfect. Thanks so much!
Chatbot: You’re welcome! Feel free to ask if you need more details on feature engineering or model architecture. **Chatbot:** You’re welcome! Feel free to ask if you need more details on feature engineering or model architecture.
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