Hello,

I want to create an AI model to learn about AI/ML. so I have scraped some data from Threads and Instagram.now I am wondering how can I use this dataset to make an AI model or do something useful with it? (BTW I don’t know anything about AI/ML. I have done internship as Data Analyst so I know a little bit about Linear regression etc. but don’t know anything advance.)

I am really curious to explore this space :)

  • lurch (he/him)@sh.itjust.works
    68·
    6 months ago

    Creating an AI Model: A Beginner’s Guide

    Introduction

    Creating an AI model involves several steps, especially if you’re new to the field. Let’s break down the process into actionable steps:

    1. Data Preprocessing:

      • Clean and preprocess your dataset.
      • Handle missing values, duplicates, and format the data appropriately.

    2. Define Your Problem:

      • Decide what task your AI model should perform (classification, regression, etc.).
      • Collect labeled data if needed (e.g., sentiment analysis).

    3. Choose an AI/ML Approach:

      • Start with simpler models before diving into deep learning.
      • Common approaches:
        • Linear Regression: Predict continuous values.
        • Classification: Assign labels to data points.
        • Clustering: Group similar data points.
        • Decision Trees: Simple yet powerful.
        • Random Forests: Ensemble of decision trees.
        • Neural Networks: Deep learning models.

    4. Feature Engineering:

      • Extract relevant features from your data.
      • Use techniques like TF-IDF or word embeddings for text data.
      • For images, consider pre-trained CNNs.

    5. Split Your Data:

      • Divide your dataset into training and validation/test sets.

    6. Train Your Model:

      • Use libraries like Scikit-Learn (for traditional ML) or TensorFlow/Keras (for deep learning).
      • Start with a simple model and iterate.

    7. Evaluate and Tune:

      • Use appropriate evaluation metrics (accuracy, precision, recall, F1-score, etc.).
      • If performance is low, consider hyperparameter tuning.

    8. Deployment:

      • Deploy your model (web app, API, etc.).

    9. Learn Continuously:

      • AI/ML is evolving; keep learning and stay updated.

    Remember, patience and persistence are key! Start small, learn, and gradually build your expertise. Good luck! 😊

    If you have any specific questions or need further guidance, feel free to ask! 🚀

    For additional resources, explore tutorials and videos on web scraping and AI model training. Happy learning! 🌟

    : Web scraping and AI model training: Microsoft Learn : Building custom models with AI Builder: Microsoft Learn : Web scraping for data models: Towards Data Science