SinoLewis / ai-basics

Generating stock reports using OpenAI GPT-4, retrieving recent finance news in Interactive Brokers, and accessing indexed data using LLama index for GPT-4 analysis.

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AI-Basics πŸ€–

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Welcome to the AI-Basics project! This project aims to provide a comprehensive introduction to basic Machine Learning (ML) concepts. Whether you're a beginner or looking to refresh your knowledge, AI-Basics has got you covered. πŸš€

Project Overview 🌟

AI-Basics is a collection of Jupyter notebooks that cover fundamental Machine Learning concepts. These notebooks are designed to be interactive and educational, guiding you through the concepts step-by-step. The project is divided into different modules, each focusing on a specific topic.

ML Concepts covered πŸ“‘

  1. Introduction to Machine Learning πŸ€“
  2. Data Preprocessing πŸ“Š
  3. Linear Regression πŸ“ˆ
  4. Classification Techniques πŸ“
  5. Clustering Algorithms 🌌
  6. Neural Networks and Deep Learning 🧠

Getting Started πŸš—

To get started with AI-Basics, follow these steps:

  1. Clone the Repository:

    git clone https://github.com/SinoLewis/ai-basics.git
  2. Navigate to the Project Folder:

    cd ai-basics
  3. Set Up Environment: We recommend using a virtual environment. Create one and install the required dependencies:

    virtualenv venv
    source venv/bin/activate  # On Windows: venv\Scripts\activate
    pip install -r requirements.txt
  4. Launch Jupyter Notebooks: Launch Jupyter in your browser and explore the notebooks:

    jupyter notebook
  5. Use Local and Google Colab Notebooks: You can run the notebooks locally or on Google Colab for free. Links to Colab notebooks are provided in each module.

Jupyter Notebooks Cheeat Sheet πŸš€

Setup 🧠

  1. Install Python: If Python is not already installed on your Debian system, you can install it using the following command:
sudo apt-get install python3
  1. Install Jupyter Notebook: You can install Jupyter Notebook using the following command:
sudo apt-get install jupyter-notebook
  1. Start Jupyter Notebook:

By default, the Jupyter Notebook server runs on port 8888.

jupyter-notebook --port=8000```

ShortCut Keys 🌈

  • Shift + Enter: Run the current cell and move to the next cell
  • Ctrl + Enter: Run the current cell and stay on the same cell
  • Alt + Enter: Run the current cell and insert a new cell below
  • Esc: Enter command mode (where you can navigate and edit cells, but not enter text)
  • Enter: Enter edit mode (where you can edit the contents of a cell)
  • A: Insert a new cell above the current cell
  • B: Insert a new cell below the current cell
  • M: Convert the current cell to a Markdown cell
  • Y: Convert the current cell to a code cell
  • D, D: Delete the current cell
  • Z: Undo the last cell operation
  • Ctrl + S: Save the notebook
  • Shift + Up: Select multiple cells above the current cell
  • Shift + Down: Select multiple cells below the current cell
  • Shift + M: Merge the selected cells
  • Shift + L: Toggle line numbers
  • Ctrl + Shift + -: Split the current cell at the cursor position
  • Esc, F: Find and replace within the notebook
  • Esc, O: Toggle cell output

Contributions and Feedback 🀝

Contributions are welcome! If you find any issues or want to enhance the content, feel free to create a pull request. We also appreciate feedback and suggestions to improve the learning experience.

Let's Dive In! πŸŽ‰

Now that you're all set up, it's time to dive into the fascinating world of AI and Machine Learning with AI-Basics! πŸ€“πŸŽˆ

Happy Learning! πŸ§ πŸ’‘

License: MIT


Note: This README is purely creative and for illustrative purposes, and the mentioned repository, links, and commands may not be real.

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Generating stock reports using OpenAI GPT-4, retrieving recent finance news in Interactive Brokers, and accessing indexed data using LLama index for GPT-4 analysis.

License:MIT License


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