Self-RAG is a new framework to train an arbitrary LM to learn to retrieve, generate, and critique to enhance the factuality and quality of generations, without hurting the versatility of LLMs.

Advanced RAG using RAG + LOTR + Remove Redundancy + Long Context Reorder

Imagine you are working as a data scientist at a home electronics company which manufactures state of the art smart televisions. You want to develop a cool feature in the smart-TV that can recogniz…

Robust recipes to align language models with human and AI preferences

The objective is to add some noise to the images and then use an Convolutional Autoencoder to denoise them.

Housing price prediction model using Ridge and Lasso Regression.

Building a deep neural network using TensorFlow 1.x for binary classification.

All course materials for the Zero to Mastery Deep Learning with TensorFlow course.

This case study aims to identify patterns which indicate if a client has difficulty paying their instalments which may be used for taking actions such as denying the loan, reducing the amount of lo…

Identifying Hot Leads by generating Lead Score for all leads, so that leads having higher Lead Scores can be contacted with priority for achieving Higher Lead Conversion Rate.

This python code can be used to extract data from Google Vision output. After you process your file for OCR using Google Vision, the generated text extraction can be structured and attributes can b…

Build a model to accurately predict whether the patients in the dataset have diabetes or not?

Building a model to predict demand of shared bikes. It will be used by the management to understand how exactly the demands vary with different features. They can accordingly manipulate the busines…