This repository is a comprehensive collection of projects demonstrating various concepts and implementations across Deep Learning, Machine Learning, and Natural Language Processing. Each project is designed to showcase practical applications and fundamental algorithms in the field of artificial intelligence.
chest_xray.ipynb: Pneumonia Detection using Convolutional Neural Networks (CNN).CIFAR10.ipynb: Image classification on the CIFAR10 dataset using Keras Sequential Model and CNN.flowers.ipynb: Clustering model for the Iris dataset.KerasFashion.ipynb: Image classification using Keras and a Sequential model on the Fashion MNIST dataset.PytorchFashion.ipynb: Fashion MNIST classification using PyTorch.titanic.ipynb: Regression model for the Titanic dataset to predict survival.fcc_cat_dog.ipynb: Cat/Dog image classification using deep learning techniques.
Anime_Recommender.ipynb: An anime recommendation system implementation.Candidate%20Elimination.ipynb: Implementation of the Candidate Elimination algorithm for concept learning.findS.ipynb: Implementation of the Find-S algorithm for concept learning.KNN.ipynb: K-Nearest Neighbors (KNN) algorithm implementation for classification.LinearRegression.ipynb: Predicting ice cream sales with custom loss and gradient descent for linear regression.PolynomialRegression.ipynb: Predicting housing prices using scikit-learn with polynomial regression.RandomForestRegression.ipynb: Random Forest Regression algorithm implementation.
nltk_basics.ipynb: Text preprocessing techniques using the Natural Language Toolkit (NLTK).RegexTagger.ipynb: Application of regular expressions for text tagging.TransitionalProbabilites.ipynb: Exploration of transitional probabilities, often used in models like Hidden Markov Models (HMMs).