a Wide Shelf for AI and Data Science | Resources 🍔

Advanced NLP Workshop: word-sense disambiguation with RoBERTa and text summarization with BART (Machine Learning Milan)

Visualizing Gradient Descent with Momentum in Python

SPPU BE COMP LP3 Codes - Machine Learning (ML) and Information and Cyber Security (ICS)

Vehicle Insurance Prediction

Being the most common and rapidly growing disease, Diabetes affecting a huge number of people from all span of ages each year that reduces the lifespan. Having a high affecting rate, it increases the significance of initial diagnosis. Diabetes brings other complicated complications like cardiovascular disease, kidney failure, stroke, damaging th…

Repository for The projects that i completed that was assigned in the nanodegree course.

Lets Grow More Virtual Internship Program(LGMVIP) Beginner level tasks as a Data Science Intern March-22

The global fashion industry is valued at three trillion dollars and accounts for 2 percent of the world's. GDP the fashion industry is undergoing a dramatic transformation by adopting new computer vision and Machine learning and deep learning techniques. In this case study we'll look at a hypothetical situation. We assume that if a retailer hire…

MetroPT-3 Anomaly Detection using Machine Learning and Deep Learning

Lead classification using python and logistic regression.

写过的深度学习文章以及翻译的文章等

Machine Learning Model to classify whether a Mushroom is Edible or Poisonous by its features

An end-to-end project which includes statistical analysis and price prediction of the laptops available in June 2022.

Google BigQuery Tutorial

"A lightweight, foundational machine learning framework implemented in Python. Features a modular design with customizable layers and support for various activation functions, as well as popular machine learning algorithms. Ideal for educational purposes and rapid prototyping." - ChatGPT Definition

Deploy a Machine Learning model into production using Docker

This system utilizes Optical Character Recognition (OCR) extracts text, while computer vision techniques map document layout. Then, SIFT (Scale-Invariant Feature Transform) cleverly matches documents to pre-defined templates, even with variations. This intelligent matching helps identify potential fraud for further investigation.