🚀 Machine Learning Hands-On Projects

Getting introduced to Machine Learning (ML) and making Hands-On Projects using Python and Google Colab.

This repository contains various beginner-to-intermediate level ML and Data Science projects implemented in Jupyter notebooks.

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📂 Repository Structure

• Diwali_Sales_Analysis.ipynb
  Exploratory Data Analysis (EDA) on Diwali sales dataset to understand customer behavior and sales trends.

• FINE_TUNE_MODEL.ipynb
  Fine-tuning pre-trained models for custom tasks.

• LionelMessiQnA.ipynb
  A Q&A project (NLP-based) focusing on Lionel Messi-related data.

• Processing_image_data_for_Deep_Learning.ipynb
  Preprocessing and handling image datasets for deep learning applications.

• WikipediaArticle_Summarizer.ipynb
  Automatic text summarizer for Wikipedia articles using NLP techniques.

• YoutubeVideo_Summarizer.ipynb
  Summarizing YouTube videos by extracting and processing transcripts.

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🛠️ Tools & Technologies

• Python 3
• Google Colab (for GPU/TPU acceleration)
• Machine Learning & Deep Learning Libraries:
  • NumPy, Pandas, Matplotlib, Seaborn
  • Scikit-learn
  • TensorFlow / PyTorch
  • NLTK / Transformers (for NLP tasks)

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🎯 Goals

• Gain hands-on experience with ML workflows.
• Learn how to preprocess, train, and evaluate ML/DL models.
• Work on real-world datasets and problem statements.