Data-Science-Lab

1. AI Agents :- All CrewAI Agents that I have created as a part of learning to build AI Agents.
2. Agentic Project :- A RAG Project for test case generator.
3. Core Concepts :- Python Core Concepts related to AI implemened on Jupyter Notebook. Blogs are posted on hashnode. Link is pasted at the end of this Readme file.
4. Gen AI :- Course notes from Google Prompt Engineering Course with Vertex AI.
5. Practice Lab 1 :- For the introductory purpose, make a machine learning model which is supposed to predict who survived during the titanic shipwreck.
6. Lab 1 :- Build your first Neural Network to predict house prices with Keras.
7. Lab 2 :- The EMNIST dataset is a set of handwritten character digits derived from the NIST Special Database 19 and converted to a 28x28 pixel image format and dataset structure that directly matches the MNIST dataset. Use Tensorflow to predict the pixelated alphabet and show its accuracy.
8. Lab 3 :- Implement basic logic gates using Hebbnet neural networks.
9. Lab 4 :- Implement Zipf's Law of Length, Law of Meanings and Heap Law.
10. Lab 5 :- Text classification for Sentimental analysis using KNN. Note: Use twitter data.
11. Lab 6 :- Case Study :- Sentiment Analysis via Reviews.
12. The Project :- A big agentic capstone project. (RAG + MCP + AI Agents)

Link to the blog : https://learnaimldswithsk.hashnode.dev/