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1. Training-a-Lunar-Lander-Agent-with-Deep-Q-Network Training-a-Lunar-Lander-Agent-with-Deep-Q-Network Public

   Training an agent with Deep-Q Network to solve the LunarLander environment in the `gymnasium` Reinforcement Learning playground (previously known as OpenAI gym)

   Python

2. Training-a-Taxi-Agent-with-Q-Learning Training-a-Taxi-Agent-with-Q-Learning Public

   Training a Taxi Agent with Q-Learning

   Python

3. Training-CartPole-agent-with-REINFORCE-policy-gradient-method Training-CartPole-agent-with-REINFORCE-policy-gradient-method Public

   Training an agent to balance in `gymnasium`'s CartPole environment with REINFORCE policy gradient method

   Python

4. Generate-Sketch-Drawings-with-Sketch-RNN-Variational-Autoencoder-Model Generate-Sketch-Drawings-with-Sketch-RNN-Variational-Autoencoder-Model Public

   Deep learning model that trains on a dataset of human-drawn sketches of a subject (e.g. bicycle, cat, etc.) and then generates new sketches of that subject.

   Python 2

5. Extractive-question-answering-with-BERT-model-fine-tuned-on-the-SQuAD-dataset Extractive-question-answering-with-BERT-model-fine-tuned-on-the-SQuAD-dataset Public

   Finetuning a BERT model on the SQuAD dataset for the task of extractive question answering.

   Jupyter Notebook

6. Generate-Image-Caption-with-ResNet-Encoder-and-LSTM-Decoder Generate-Image-Caption-with-ResNet-Encoder-and-LSTM-Decoder Public

   Generate a sentence to describe an image, using ResNet encoder to extract image features and LSTM decoder to translate latent features into captions.

   Python 1