Telegram Group & Telegram Channel
🚀 Train Loan Prediction Models with Synthetic Data using CTGAN
📊 | #FinTech #MachineLearning #DataScience #SyntheticData #CTGAN

In real-world financial environments, access to high-quality, privacy-compliant loan data can be extremely limited due to regulatory and ethical constraints.

That’s why in my latest FinTech ML project, I explore how to train accurate loan prediction models using synthetic datasets generated by CTGAN (Conditional Tabular GAN).

đź’ˇ Why this matters:

Maintain data privacy without sacrificing model realism

Generate diverse borrower profiles and edge cases

Build ML-ready datasets with class balance and feature richness

🔍 What’s covered:

Simulate loan application data (income, credit score, loan amount, status, etc.)

Generate synthetic records using CTGAN from SDV

Train and evaluate classification models (XGBoost, RandomForest)

Compare real vs synthetic model performance

đź›  Tools: Python, Pandas, CTGAN, Scikit-learn, Matplotlib


Let’s advance ethical AI in finance—one synthetic sample at a time.
đź’¬ Curious to try synthetic data in your projects? Drop your thoughts or questions below!
https://youtu.be/cqGLJsOpNPU
👍5



group-telegram.com/epythonlab/1995
Create:
Last Update:

🚀 Train Loan Prediction Models with Synthetic Data using CTGAN
📊 | #FinTech #MachineLearning #DataScience #SyntheticData #CTGAN

In real-world financial environments, access to high-quality, privacy-compliant loan data can be extremely limited due to regulatory and ethical constraints.

That’s why in my latest FinTech ML project, I explore how to train accurate loan prediction models using synthetic datasets generated by CTGAN (Conditional Tabular GAN).

đź’ˇ Why this matters:

Maintain data privacy without sacrificing model realism

Generate diverse borrower profiles and edge cases

Build ML-ready datasets with class balance and feature richness

🔍 What’s covered:

Simulate loan application data (income, credit score, loan amount, status, etc.)

Generate synthetic records using CTGAN from SDV

Train and evaluate classification models (XGBoost, RandomForest)

Compare real vs synthetic model performance

đź›  Tools: Python, Pandas, CTGAN, Scikit-learn, Matplotlib


Let’s advance ethical AI in finance—one synthetic sample at a time.
đź’¬ Curious to try synthetic data in your projects? Drop your thoughts or questions below!
https://youtu.be/cqGLJsOpNPU

BY Epython Lab


Warning: Undefined variable $i in /var/www/group-telegram/post.php on line 260

Share with your friend now:
group-telegram.com/epythonlab/1995

View MORE
Open in Telegram


Telegram | DID YOU KNOW?

Date: |

The next bit isn’t clear, but Durov reportedly claimed that his resignation, dated March 21st, was an April Fools’ prank. TechCrunch implies that it was a matter of principle, but it’s hard to be clear on the wheres, whos and whys. Similarly, on April 17th, the Moscow Times quoted Durov as saying that he quit the company after being pressured to reveal account details about Ukrainians protesting the then-president Viktor Yanukovych. On Telegram’s website, it says that Pavel Durov “supports Telegram financially and ideologically while Nikolai (Duvov)’s input is technological.” Currently, the Telegram team is based in Dubai, having moved around from Berlin, London and Singapore after departing Russia. Meanwhile, the company which owns Telegram is registered in the British Virgin Islands. Following this, Sebi, in an order passed in January 2022, established that the administrators of a Telegram channel having a large subscriber base enticed the subscribers to act upon recommendations that were circulated by those administrators on the channel, leading to significant price and volume impact in various scrips. These administrators had built substantial positions in these scrips prior to the circulation of recommendations and offloaded their positions subsequent to rise in price of these scrips, making significant profits at the expense of unsuspecting investors, Sebi noted. In this regard, Sebi collaborated with the Telecom Regulatory Authority of India (TRAI) to reduce the vulnerability of the securities market to manipulation through misuse of mass communication medium like bulk SMS.
from kr


Telegram Epython Lab
FROM American