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Премиум
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    Introduction
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    What We're Using
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    Jupyter Notebook
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    Google Colab
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    Getting a Gemini API Key
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    Installing the Python SDK for Gemini API and Authenticating to Gemini
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    Gemini Multimodal Models: Nano, Pro, and Ultra
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    Google AI Studio: Freeform Prompts With Gemini Pro Vision
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    Google AI Studio: Using Variables and Parameters in the Prompt
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    Generating Text From Text Inputs: Gemini Pro
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    Streaming Model Responses
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    Generating Text From Image and Text Inputs: Gemini Pro Vision
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    Gemini API Generation Parameters: Controlling How the Model Generates Responses
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    Gemini API Generation Parameters Explained
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    Building Chat Conversations
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    Project: Building a Conversational Agent Using Gemini Pro
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    Project Requirements
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    Building the Application
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    Testing the Application
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    Streamlit: Transform Your Jupyter Notebooks into Interactive Web Apps
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    Creating the Web App Layout With Streamlit
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    Saving and Displaying the History Using the Streamlit Session State
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    Project Introduction
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    Getting Images Using a Generator
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    Renaming Images Using Gemini Pro Vision
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    Intro to Prompt Engineering the Gemini API
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    Tactic #1 - Position Instructions Clearly With Delimiters
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    Tactic #2 - Provide Detailed Instructions for the Context, Outcome, or Length
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    Tactic #3 - Specify the Response Format
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    Tactic #4 - Few-Shot Prompting
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    Tactic #5 - Specify the Steps Required to Complete a Task
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    Tactic #6 - Give Models Time to "Think"
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    Other Tactics for Better Prompting and Avoiding Hallucinations
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    Prompt Engineering Summary