Welcome to the Deep Learning Repository! This repository contains various projects and assignments related to deep learning implemented using Python and popular deep learning libraries such as TensorFlow and Keras.
Bajaj Finance-RNN-GRU.ipynb - This project implements a recurrent neural network (RNN) with Gated Recurrent Units (GRU) to analyze financial data from Bajaj Finance.
Bank_Intend_LSTM.ipynb - In this project, a Long Short-Term Memory (LSTM) model is used to classify banking customer intents based on textual data.
BrainTumor.ipynb - This project focuses on using deep learning techniques to detect and classify brain tumors from MRI images.
Convoutional_neural_network.ipynb - Implementing a convolutional neural network (CNN) for image classification tasks using the Fashion MNIST dataset.
Covid_RNN_GRU(MODEL).ipynb - A project where a recurrent neural network (RNN) with GRU cells is trained to predict the spread of COVID-19.
Deep_Learning_Assignment.ipynb - This notebook contains a collection of deep learning assignments covering various topics such as neural network architectures, optimization algorithms, and more.
Fashion MNIST Model.ipynb - An implementation of a deep learning model using TensorFlow/Keras to classify fashion items in the Fashion MNIST dataset.
Intent_Detection_LSTM.ipynb - A project where an LSTM model is trained to detect intents in natural language text for use in chatbot applications.
Linear Regression and Sigmoid Neuron Implementation - This assignment involves implementing linear regression and a single sigmoid neuron from scratch using Python and NumPy.
Perceptron Function(Practical-1).ipynb - An assignment focusing on the implementation and understanding of the perceptron function.
Perceptron Model(Practical-2).ipynb - Another assignment covering the implementation and training of a perceptron model for binary classification tasks.
This repository is licensed under the MIT License.