Arthur KAZA's Projects
The alternative credit risk model focuses on the target group of customers with little or no credit history to evaluate customer credit risk assessment on the basis of other relevant feature points in modern times like utility payments data, social media profile, psychometric test,etc and create an alternate credit score
Argon Dashboard - Flask Template | Creative-Tim
Config files for my GitHub profile.
A ChatGPT-powered Medical Diagnosis Assistant Experience
Enable Next-Gen Large Language Model Applications. Join our Discord: https://discord.gg/pAbnFJrkgZ
A decentralised credit scoring service based on blockchain which employs deep learning to calculate an intelligent credit score based on the credit history, delinquencies and 73 other parameters which are usually accounted while calculating a comprehensive credit score to promote collaboration among banks
For this challenge, I have completed the code to classify images of dogs and cats. I used Tensorflow 2.0 and Keras to create a convolutional neural network that correctly classifies images of cats and dogs at least 63% of the time.
Implementation of Channel Attention in PyTorch
A decentralised credit scoring platform based on Multichain blockchain
深度学习在推荐系统中的应用及论文小结。
A document classifier machine learning model analyzes documents and tags them with the appropriate label from a set of labels that you define. Classifying documents is useful when you want to sort many documents into groups programmatically.
DroneKit-Python library for communicating with Drones via MAVLink. readthedocs.org/projects/dronekit-python
DroneKit-Python library for communicating with Drones via MAVLink. readthedocs.org/projects/dronekit-python
This Python script extracts tables containing specific keywords, such as "Revenue" and "Income," from a collection of PDF files in the specified input directory and saves the extracted tables as Excel files in the specified output directory.
Certain approaches are common to the exploration of all financial data, such as using time-series analytic methods, and in the treatment of missing data. It would be simplistic, however, to treat all financial data in the same way.
Flask API exposing an endpoint for determining the sentiment of text.
This app is a simple example of using Streamlit to create a financial data web app. This demo use streamlit, pandas and yfinance modules. Allows you to select one of the 500 companies that compose the S&P 500 and display a updated chart of adjusted closing prices, as well as add a pair of moving averages.
Python script to extract as much structured information as possible from annual/quarterly reports.
Made with streamlit at least it will be one of the powerful business IA agent CRM using GPT 3.5 Turbo for mailing, fit gap and feedbacks
Made with Flask at least it will be one of the powerful business IA agent CRM using GPT 3.5 Turbo for mailing, fit gap and feedbacks
Interaction with an insta bot
Bot to facilitate interactions on LinkedIn
A fully trained machine learning model can then be used to make predictions for new instances.
First Party data integration solution built for marketing teams to enable audience and conversion onboarding into Google Marketing products and Facebook Ads
This is actually the hardest problem to me among all 5 final projects of the AI course. This probably is cheating, but I learn the idea for the solution from Milk's solution. I don't who implement the abby player, but it's really hard to beat.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent