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1. Introduction-to-Monte-Carlo-Methods Introduction-to-Monte-Carlo-Methods Public

   This course examines the Monte Carlo methods and its types and solves the frozen lake problem with Monte Carlo methods.

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2. Hotspot-Analysis Hotspot-Analysis Public

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3. Web-Scraping-with-Jupyter-Notebooks Web-Scraping-with-Jupyter-Notebooks Public

   Analyze and parse HTML responses, programmatically scrape web data, and utilize Pandas DataFrames to store, transform, and merge tables.

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4. Using-Text-Generators-and-Summarization-models Using-Text-Generators-and-Summarization-models Public

   Generate and paraphrase text using different models for use in Python. Understand the applications and challenges of text summarization models.

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5. Playing-an-Atari-Game-with-Deep-Recurrent-Q-Networks Playing-an-Atari-Game-with-Deep-Recurrent-Q-Networks Public

   This module will look at how to build different variants of DRQN including DARQN to solve the problem of Atari game

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6. Markov-Decision-Processes-and-Bellman-Equations Markov-Decision-Processes-and-Bellman-Equations Public

   The module covers the theory behind reinforcement learning and introduces Markov chains and Markov Decision Processes

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