HenryHengLUO /
Retrieval-Augmented-Generation-Intro-Project
This project aims to introduce and demonstrate the practical applications of RAG using Python code in a Jupyter Notebook environment.
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euansmith9 / repository
This project demonstrates how to extract and structure financial data using web scraping techniques in Python. It focuses on collecting GameStop and Tesla's quarterly revenue from HTML sources using requests, BeautifulSoup, and pandas, and presents the data in clean, tabular form within a Jupyter Notebook.
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HenryHengLUO /
This project aims to introduce and demonstrate the practical applications of RAG using Python code in a Jupyter Notebook environment.
68/100 healthDIGVISHRAYALA /
This repository contains a Jupyter Notebook developed as part of the CA-2 project. It focuses on data analysis using Python with libraries like Pandas, NumPy, Matplotlib, and others. The project demonstrates data loading, preprocessing, exploration, and visualization techniques suitable for academic submissions or real-world data insights.
47/100 healthJeetjha-07 /
A Machine Learning project that predicts Total Sales, Sales Method, and Units Sold using Linear Regression, Decision Trees, and Random Forest. This project also demonstrates complete DevOps workflow using Git & GitHub — including branching, merging, stashing, and rebasing — with a clean project structure and Jupyter notebook-based analysis
63/100 healthNimraAslamkhan /
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow is a comprehensive machine learning project that guides users through the implementation of various algorithms and techniques, from basic linear regression to complex deep learning models. This repository includes code examples and Jupyter notebooks that demonstrate the concepts cov
57/100 healthrubenandrebarreiro /
⚛️ 🔒 🔑 A project based in Cryptography, most specifically in Quantum Cryptography. This project was built using Python, Jupyter Notebook, and some Quantum Frameworks, such as, Qiskit (IBM Q Experience), Cirq (Google AI Quantum), PyQuil (Rigetti Computing), PennyLane (Xanadu Quantum Technologies), Q# (Microsoft Quantum Development Kit), ProjectQ (ETHZ's Quantum Open-Source Framework), Quantum Inspire (TU Delft's Quantum Platform) and QuTip. It's made a brief introduction to Quantum Computing, then explained a little of the background history of the BB84 Protocol, how it works, possible practical implementations/solutions, its security proofs, comparisons with other Classical Key Distribution schemes and demonstrated a couple of Live Demos of it.
64/100 healthmaxzaikin /
Hello and welcome to my Data Science portfolio! This repository serves as a central hub showcasing a collection of my projects demonstrating skills and experience in data analysis, machine learning, and artificial intelligence. Each project folder contains Jupyter Notebooks with detailed code, explanations, and visualizations.
63/100 health