Welcome to my Lab Programs Repository, featuring hands-on projects in:
- 🧠 Generative AI
- 📊 Machine Learning
This repo contains practical Python programs and Jupyter notebooks that showcase modern AI & ML techniques using real-world datasets and modern APIs.
lab-programs/
├── Gen-AI/
│ ├── 1_explore_pretrained_word_vectors.py
│ ├── 2_visualize_word_embeddings_dimensionality_reduction.py
│ ├── 3_train_custom_word2vec_domain_specific.py
│ ├── 4_enrich_prompt_with_embeddings.py
│ ├── 5_generate_sentences_from_embeddings.py
│ ├── 6_sentiment_analysis_huggingface.py
│ ├── 7_summarize_text_huggingface.py
│ └── 8_cohere_chat_example.py
├── ML-Lab/
│ ├── ML_Lab.ipynb
│ └── ML-Lab-datasets/
│ ├── auto-mpg.csv
│ ├── BostonHousing.csv
│ ├── breastcancer_modified.csv.csv
│ ├── california_housing.csv
│ ├── Filtered_Students.xlsx
│ ├── heart.csv
│ ├── housing.csv
│ ├── iris.csv
│ └── olivettifaces.mat
| Program No. | Task |
|---|---|
| 1 | Explore Pre-trained Word Vectors |
| 2 | Visualize Word Embeddings (Dimensionality Reduction) |
| 3 | Train Custom Word2Vec on Domain Data |
| 4 | Enrich Prompts with Embeddings |
| 5 | Generate Sentences from Embeddings |
| 6 | Sentiment Analysis using HuggingFace Transformers |
| 7 | Text Summarization using HuggingFace Transformers |
| 8 | Chat Example with Cohere API |
| Component | Description |
|---|---|
| ML_Lab.ipynb | End-to-end ML notebook covering data preprocessing, visualization, and model training |
| Datasets | 9+ diverse datasets included for ML experimentation |
git clone https://github.com/Dev-0618/Lab-Programs.git
cd Lab-Programspip install -r requirements.txtcd Gen-AI
python 1_explore_pretrained_word_vectors.py
# or any other programcd ML-Lab
jupyter notebook ML_Lab.ipynb- Python 3.x
- HuggingFace Transformers
- Cohere API
- Word2Vec (Gensim / custom training)
- Scikit-learn
- Pandas
- Matplotlib / Seaborn
- Jupyter Notebooks
Contributions are welcome! Feel free to fork this repo and submit pull requests to improve or extend the projects.
Crafted with ❤️ by [Dev-0618](https://github.com/Dev-0618)