JaewonSon37/Neural_Networks_and_Deep_Learning1

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yonteels/Number-Detection

This is a custom-built neural network that detects handwritten numbers from image inputs. It uses ReLU activation in the hidden layers and a softmax activation function in the output layer for classification. The model is trained using backpropagation with a loss function to minimize prediction errors, achieving over 99% accuracy when predicting di

Language: Python - Size: 791 KB - Last synced at: 10 days ago - Pushed at: 10 days ago - Stars: 0 - Forks: 0

Rex-8/MNIST-4-layer

Implementing a 4 layer neural to identify digits from a 28x28 grid using just python and numpy

Language: Python - Size: 107 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 0

MohammedSaqibMS/Gradient-Checking

Gradient Checking: Demonstrates 1D and ND gradient checking techniques to verify the accuracy of gradients in neural networks. Inspired by DeepLearning.AI's Deep Learning Specialization.

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Lin-TzuLing/NYCU-DLP-2023

Deep Learning & Labs Course, NYCU, 2023

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marcelogcardozo/migracao-sismica

Desenvolvimento de ferramenta para efetuar a Modelagem e a Migração Sísmica de um modelo 2D.

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PPPW/deep-learning-random-explore

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mattsankner/micrograd

I build the Micrograd autogradient engine, which is a functioning neural network with forward pass, backward propagation, and stochastic gradient descent, all built from scratch. This is derived from the great @karpathy micrograd lecture. Each notebook is complete with Andrei's lecture code and speech, as well as my own code, anecdotes and addition

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dhwabqryh/Data-Mining-I

Tugas praktikum Data Mining I

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muhammadshaffay/Text-Clipper

A tool that quickly and accurately segments Urdu sentences and words in your text.

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LiYan-97/CG_SF64

This code uses computational graph and neural network to solve the five-layer traffic demand estimation in Sioux Falls network. It also includes comparison of models and 10 cross-validations.

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yizt/numpy_neural_network

仅使用numpy从头开始实现神经网络,包括反向传播公式推导过程; numpy构建全连接层、卷积层、池化层、Flatten层；以及图像分类案例及精调网络案例等,持续更新中... ...

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brian00715/CNN-From-Scratch

A.K.A. NUS ME5411 Final Project. Implemented a CNN framework without off-the-shelf libraries and its application for character recognition.

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aadityasikder/Neural-Network-from-Scratch-

This notebook demonstrates a neural network implementation using NumPy, without TensorFlow or PyTorch. Trained on the MNIST dataset, it features an architecture with input layer (784 neurons), two hidden layers (132 and 40 neurons), and an output layer (10 neurons) with sigmoid activation.

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Eruimdas/Basics-of-Computational-Graph

A simple mimicking of TensorFlow, which including forward and backward propogation.

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iforever-yh/BP_FittingTool

Fit functions using the Backpropagation Algorithm. 一个使用反向传播算法拟合函数的工具。

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Amber0914/NN_without_libraries

It's a demonstration for implementing NN without using any deep learning library.

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Tensor-Array/Tensor-Array

A C++ machine learning framework/library.

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oselin/gradient_ML_LTI

A gentle introduction to custom gradient propagation for ML application in which parameters of LTI systems have to be optimized. This example enables the integration of control theory with machine learning, for the development of Physical-Informed Neural Networks (PINNs)

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Apoorv070/Deep_learning_Basics

Learning about Perceptron and Multi layered perceptron

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sef007/Neural-Network-Email-Classifier-Numpy-Only

Neural Network using NumPy, V1: Built from scratch. V2: Optimised with hyperparameter search.

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chiapeilin/Neural-Network

The code of forward propagation , cost function , backpropagation and visualize the hidden layer.

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hellonlp/deep-learning

搭建、深度学习、前向传播、反向传播、梯度下降和模型参数更新、classification、forward-propagation、backward-propagation、gradient descent、python、text classification

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slothengineer/DeepLearning-Concepts

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xujiachang1024/NumPy-based-Neural-Network

A highly modular design and implementation of fully-connected feedforward neural network structured on NumPy matrices

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sef007/NN-Numpy-Only-HOG-Feature-Extraction-and-ML-Library-Integration

Digit Recognition Neural Network: Built from scratch using only NumPy. Optimised version includes HOG feature extraction. Third version utilises prebuilt ML libraries.

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xahid007/Neural-Netowork

In this repo, I tried to upload basic components of Neural Network. It will eventually help to understand the core ideas of NN.

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ErniW/Neural-Network-in-pure-NumPy

A feedforward neural network from scratch without any high level deep learning libraries. Pure mathematics and NumPy.

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grvnair/rnn-using-numpy

Built a simple RNN Model using NumPy

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MBadriNarayanan/DeepLearningSpecializationCoursera 📦

Deep Learning Specialization (5 Courses) . Course offered by deeplearning.ai and Coursera. Taught by Andrew Ng.

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yashsriram/spnn

A comparison of fully connected network (forward and backward propagation) implementations.

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navjindervirdee/neural-networks

Implemented Convolutional Neural Network, LSTM Neural Network, and Neural Network From Scratch in Python Language.

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mohadeseh-ghafoori/develop-DNNs

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mohadeseh-ghafoori/cat-detection-with-Logistic-Regression

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mohadeseh-ghafoori/NNs-with-one-hidden-layer

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mohadeseh-ghafoori/Recurrent-Neural-Networks-with-LSTM

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ajaybiswas22/Neural-Network-Logic-Gates

This repository provides the Implementation of logic gates using neural networks.

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CICIFLY/Deep-Learning-Projects

CNN, ANN, Python, Matlab

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janivkk/neural-network

Artificial Intelligence - Assessment 1

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SoniSiddharth/ML-Logistic-regression-Neural-Networks-from-scratch

Logistic Regression and Neural Networks implementation from scratch

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CS-Ponkoj/Cat-Recognition-Logistic_Regression_with_a_Neural_Network_mindset

This is a project to recognize cat using logistic regression with Neural Network concepts of backward and forward propagation from DeepLearning.AI.

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hasanur-rahman/AI-Scratch-Projects

I have implemented some AI projects from scratch implementation without explicit use of the built-in-libraries and thus added to this repo.

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nareshkumar66675/Neuron

A Neural Network Architecture

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DunittMonagas/Neural-Networks-and-Deep-Learning

Curso Neural Networks and Deep Learning. Primer curso del programa especializado Deep Learning. Este repositorio contiene todos los ejercicios resueltos. https://www.coursera.org/learn/neural-networks-deep-learning

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