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ml/cc
ml/cc
 
 
Binary_Neural_Network.ipynb
Binary_Neural_Network.ipynb
 
 
Build Smarter AI Apps Empower LLMs with LangChain.ipynb
Build Smarter AI Apps Empower LLMs with LangChain.ipynb
 
 
Building AI Agents from Scratch - Weather Agent Daily Dish.ipynb
Building AI Agents from Scratch - Weather Agent Daily Dish.ipynb
 
 
CoffeeRoasting_TensorFlow.ipynb
CoffeeRoasting_TensorFlow.ipynb
 
 
Cost_Function_Soln.ipynb
Cost_Function_Soln.ipynb
 
 
DSCN0732.JPG
DSCN0732.JPG
 
 
Decision_Tree.ipynb
Decision_Tree.ipynb
 
 
Differentiation_in_Python.ipynb
Differentiation_in_Python.ipynb
 
 
EDA.ipynb
EDA.ipynb
 
 
Eigen_values_matrices.ipynb
Eigen_values_matrices.ipynb
 
 
FeatEng_PolyReg.ipynb
FeatEng_PolyReg.ipynb
 
 
Feature_Scaling_and_Learning_Rate.ipynb
Feature_Scaling_and_Learning_Rate.ipynb
 
 
In-Context Learning and Prompt Templates for Advanced AI.ipynb
In-Context Learning and Prompt Templates for Advanced AI.ipynb
 
 
Intro-to-Pandas_EDA.ipynb
Intro-to-Pandas_EDA.ipynb
 
 
LLM-Powered Data Science LCEL.ipynb
LLM-Powered Data Science LCEL.ipynb
 
 
Linear_Regression.ipynb
Linear_Regression.ipynb
 
 
Linear_transforms.ipynb
Linear_transforms.ipynb
 
 
Logistic_Regression.ipynb
Logistic_Regression.ipynb
 
 
Model_Evaluation_and_Selection.ipynb
Model_Evaluation_and_Selection.ipynb
 
 
Model_Representation_Soln.ipynb
Model_Representation_Soln.ipynb
 
 
Monty_Hall_problem.ipynb
Monty_Hall_problem.ipynb
 
 
Multiclass_Neural_Network.ipynb
Multiclass_Neural_Network.ipynb
 
 
Multiple_Variable_Soln.py
Multiple_Variable_Soln.py
 
 
Naive_Bayes.ipynb
Naive_Bayes.ipynb
 
 
RAG with Hugging Face.ipynb
RAG with Hugging Face.ipynb
 
 
RAG with Pytorch.ipynb
RAG with Pytorch.ipynb
 
 
README.md
README.md
 
 
Recommender_SysNN_Assignment.ipynb
Recommender_SysNN_Assignment.ipynb
 
 
Rideshare_Project_Week1.ipynb
Rideshare_Project_Week1.ipynb
 
 
Sklearn_GD.ipynb
Sklearn_GD.ipynb
 
 
Summarize private documents using RAG LangChain and LLMs.ipynb
Summarize private documents using RAG LangChain and LLMs.ipynb
 
 
Tree_Ensemble.ipynb
Tree_Ensemble.ipynb
 
 
Vector_Operations.ipynb
Vector_Operations.ipynb
 
 
matrices.ipynb
matrices.ipynb
 
 

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A collection of Jupyter notebooks exploring Python programming concepts, machine learning, deep learning, AI AGENTS and computational techniques.

Overview

This repository contains educational and exploratory Jupyter notebooks written in Python. Each notebook is designed to be self-contained and focuses on specific topics, from fundamental Python concepts to advanced data science techniques.

Purpose

  • Learn & Explore: Hands-on notebooks for learning Python and data science
  • Experimentation: A space to test ideas and prototype solutions
  • Reference: Reusable code snippets and examples for common tasks
  • Documentation: Well-commented code with explanations and visualizations

Getting Started

Prerequisites

  • Python 3.7+
  • Jupyter Notebook or JupyterLab
  • Required packages (see Dependencies)

Installation

  1. Clone the repository:
git clone https://github.com/jiyajain23/py-notebooks.git
cd py-notebooks

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