Mnist digits recognition using tensorflow

Linear Regression, Logistic Regression, Neural Networks with Back Propagation

Implementation of Artificial Neural Networks in MATLAB and Python.

Making Neural network model from scratch for prediction of digit classification. Its built from scratch using feedforward and backpropagation loops using numpy arrays.

Real-time Neural Style Transfer

Thử Nghiệm Neuron Network với MNIST Datasets

This is heart disease prediction project that contains different methods such as FNN with Multiclass Classification, Binary Classification, Cross-Validation etc.

Deep learning methods for sentiment analysis classification of covid-19 vaccination tweets

Harmonizing Hearts: A Music-Based Compatibility Analysis

Develop and test a feedforward neural network for handwritten digit recognition using PyTorch and the MNIST benchmark dataset

This Repository consists of programs related to AI-ML-DL-NLP-CV. Few examples include - KNN, Naive Bayes, Decision Trees, EDA etc.

Feedforward Neural Network Implementation (pure numpy)

Simple feedforward neural network with back-propagation implemented in java.

Deep Learning from basic to advance level include Bert for text intent classification

Implementation of feed forward computation from scratch

Activation function, feed forward network, Training a Neural Network, Error and Loss Function, Optimization, Backpropagation, Early stopping, Model Saving

Leveraging the mapreduce paradigm we propose a solution to parallelize the feedforward operation of neural networks in order to speed it up for sufficiently large NN architectures and for sufficiently large datasets. Tested Using the MNIST dataset results can be found in the results.html and results.ipynb files.

Explore CIFAR10 dataset through creating a Feed Forward Neural Network, training a CNN from scratch, and implementing advanced techniques like data normalization, augmentation, and ResNets in PyTorch to achieve over 90% accuracy.

The repository contains all the codes of all practicals of ANN (SL-2) lab for the AIDS branch. The codes are according to problem statements given in the syllabus of SPPU. Download code and practice them to score good in your practical exams :)