Multi-Agent Financial Research workflow
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Updated
Mar 26, 2026 - Jupyter Notebook
Multi-Agent Financial Research workflow
An Application acts as a guide for the common people in locating a financial service touch point at a given location in the country.
In this project I have performed analysis and prediction on 1,3,and 5 year returns on 1064 mutual funds in India. I have scraped data from a website which is the most visited website for mutual fund investments.I have tested regression models linear model,SGD Regressor , Random Forest Regressor,Decision Tree Regressor,Ridge,MLP Regressor and lin…
The ultimate guide to global financial certifications (CFA, FRM, CAIA) and FinTech career paths. Bridging finance with tech architecture.
Exploratory data analysis (EDA) of bank failure datasets
# Financial Fraud Detection – Credit Card Transactions
A comprehensive credit card weekly dashboard that provides real-time insights into key performance metrics and trends, enabling stakeholders to monitor and analyze credit card operations effectively.
로컬 디바이스에 저장되어있는 증권사 리포트(PDF)의 내용을 검색할 수 있는 LangChain, LangGraph기반 AI agent
A command-line expense tracker built in Python with CSV storage, budget tracking, categories, search, sorting, and pytest test units.
I've just narrowed the scope further to ensure manageability. I am focusing on the model associations of JournalVoucher, JournalEntry, and ChartOfAccount. I'm now setting up the database context and will explain the code that supports this fundamental structure.
Web-based personal budget app to track income and expenses, manage monthly budgets, and set savings goals. It offers dashboards and reports for financial clarity, helping users control spending and make better financial decisions securely and efficiently.
Analyzed credit loan data from Kaggle. with 132 variables and 300000+ records. The aim is to find significant factors that contribute to the loan default
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