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    • Practical Reinforcement Learning using Python 8 Artificial Intelligence Agents

    Practical Reinforcement Learning using Python 8 AI Agents

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    Udemy

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    Mode

    Online

    Fees

    ₹ 799

    Quick Facts

    particular details
    Medium of instructions English
    Mode of learning Self study
    Mode of Delivery Video and Text Based

    Course and certificate fees

    Fees information
    ₹ 799
    certificate availability

    Yes

    certificate providing authority

    Udemy

    The syllabus

    Introduction

    • Introduction

    SpaceInvaders Agent

    • Setting up for course & Installing Python Packages
    • Importing Packages & Setting up Gym Environment
    • Building Neural Network
    • Building Reinforcement Learning Agent
    • Training Agent
    • Visualizing our Agent
    • Save & Load Agent

    Autonomous Taxi Agent

    • Setting up Project & Installing Python Packages
    • Importing Packages & Setting up Gym Environment
    • What is Q-Learning?
    • Implementing Q-Learning from Scratch
    • Training Q-Learning Agent
    • Analyzing our Trained Agent
    • Visualizing our Agent & Testing in other Environments

    Flappy Bird Reinforcement Learning Agent

    • Setting up Project & Installing Python Packages
    • Importing Packages
    • Building class for Flappy Bird Agent
    • What is Deep Q Learning ?
    • Building Neural Network
    • Acting Function
    • Train Function
    • Learn Function
    • Visualize Function
    • Visualize Trained Agent

    Mario Reinforcement Learning Agent

    • Setting up Project & Installing Python Packages
    • Importing Packages
    • Setting up Gym Environment
    • Building Class for Mario Agent
    • Building Neural Network
    • Act Function
    • Update Epsilon Function
    • Train Function
    • Preprocess State for Neural Network Function
    • Learn Function
    • Creating a Better Learning Environment for Agent
    • Save & Load Agent
    • Visualizing our Agent

    Stocks Reinforcement Learning Agent

    • Setting up Project & Installing Python Packages
    • Importing Packages
    • Getting our S&P 500 Data
    • Preprocessing our Data
    • Creating our Environment
    • Taking Random Actions in Environment
    • Creating Model & Learning from Environment
    • Visualizing our Agent
    • PART 2: Implementing 89 different Technical Indicators in Data
    • PART 2: Creating Environment with Technical Indicators
    • PART 2: Visualizing our Agent in TA Environment

    Car Reinforcement Learning Agent

    • Setting up Project & Installing Python Packages
    • Importing Packages
    • Agent 1) Setting up Roundabout Gym Environment
    • Agent 1) Training & Visualizing our Agent
    • Agent 2) Setting up Parking Gym Environment
    • Agent 2) Training our Agent
    • Agent 2) Visualizing our Agent
    • Agent 3) Highway Agent

    Code for Course

    • Link

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