[WIP] Add Jupyter notebook templates for various ML use cases

[Copilot]

• Create a templates/ directory for notebook templates
• Create template 1: Machine Learning Preset (general ML tasks with data preprocessing, feature engineering, model evaluation)
• Create template 2: Neural Network Model (template for setting up and training neural networks with TensorFlow/PyTorch)
• Create template 3: Language Model (template for fine-tuning and evaluating language models with Hugging Face Transformers)
• Create template 4: Sentiment Analysis Model (template for building sentiment analysis models)
• Update README.md to document the new templates
• Update requirements.txt with necessary dependencies (transformers, torch)
• Test that notebooks can be opened without errors

Original prompt

Add Jupyter notebook templates to the MLLanguageModels repository for the following use cases:

1. Machine Learning Preset: A template for general machine learning tasks, including data preprocessing, feature engineering, and model evaluation.
2. Neural Network Model: A notebook template to set up and train a neural network using popular libraries like TensorFlow or PyTorch.
3. Language Model: A Jupyter notebook template for fine-tuning and evaluating language models, leveraging frameworks like Hugging Face Transformers.
4. Sentiment Analysis Model: A template for building and testing sentiment analysis models, including data loading, preprocessing, and evaluation metrics.

Ensure these templates are well-documented, with placeholders for user customization, and include environment setup instructions.

This pull request was created as a result of the following prompt from Copilot chat.

Add Jupyter notebook templates to the MLLanguageModels repository for the following use cases:

1. Machine Learning Preset: A template for general machine learning tasks, including data preprocessing, feature engineering, and model evaluation.
2. Neural Network Model: A notebook template to set up and train a neural network using popular libraries like TensorFlow or PyTorch.
3. Language Model: A Jupyter notebook template for fine-tuning and evaluating language models, leveraging frameworks like Hugging Face Transformers.
4. Sentiment Analysis Model: A template for building and testing sentiment analysis models, including data loading, preprocessing, and evaluation metrics.

Ensure these templates are well-documented, with placeholders for user customization, and include environment setup instructions.

---

💬 Share your feedback on Copilot coding agent for the chance to win a $200 gift card! Click here to start the survey.

[Copilot]

Copilot wasn't able to review any files in this pull request.

---

_{Tip: Customize your code reviews with copilot-instructions.md. Create the file or learn how to get started.}