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Foundational AI-ML Concepts 

Almost before we knew it, we had left the ground. All their equipment and instruments are alive.Mist enveloped the ship three hours out from port. The spectacle before us was indeed sublime.A red flair silhouetted the jagged edge of a wing.

Machine Learning

A pool of good reads, all about ML at one place.

AI and its domains

A summarized document for AI and its 3 major domains.

Machine Learning Models

Read more about Supervised and Unsupervised Learning Approaches of Artificial Intelligence.

Algorithm: Introduction

Introduce yourself to the fascinating world of algorithms.

Natural Language Processing

An introduction to the AI domain of Natural Language Processing

Introduction to Python: notebook

Explore python basics through an online notebook

OpenCV

A descriptive tutorial on OpenCV package for python

AI Resource Document

A comprehensive document focusing on AI - its domains and related concepts

Advanced AI-ML Concepts 

Almost before we knew it, we had left the ground. All their equipment and instruments are alive.Mist enveloped the ship three hours out from port. The spectacle before us was indeed sublime.A red flair silhouetted the jagged edge of a wing.

CNN

Convolutional Neural Networks (CNNs) are a type of deep learning model used for image recognition and processing. They mimic the human brain’s visual perception, identifying patterns, edges, and features in images. CNNs power applications like facial recognition, object detection, and medical imaging, making them essential for AI-driven vision tasks.

"Neural functions process information, enabling learning, pattern recognition, and decision-making in AI."

VANILA RNN

A Vanilla RNN is a basic Recurrent Neural Network used for processing sequential data, like text and time series. It has a feedback loop that allows information to persist, making it useful for speech recognition, language modeling, and time-series prediction. However, it struggles with long-term dependencies due to vanishing gradients

"GRU (Gated Recurrent Unit) is a neural network optimizing memory retention in sequences."

LSTM

LSTM (Long Short-Term Memory) is an advanced type of Recurrent Neural Network (RNN) designed to handle long-term dependencies in sequential data. It uses gates (input, forget, and output) to control information flow, making it effective for speech recognition, language translation, and time-series prediction while overcoming the vanishing gradient problem.

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