https://github.com/mohammedsaqibms/optimization_methods

Description: This repository implements a 3-layer neural network to compare the performance of Gradient Descent, Momentum, and Adam optimization algorithms on a dataset, highlighting their training accuracy and convergence behavior.

adam-optimizer deep-learning gradient-descent machine-learning momentum-gradient-descent neural-networks optimization-algorithms python3

Last synced: 23 Feb 2025

https://github.com/mohammedsaqibms/planar_data_classification_with_onehidden_layer

This repository implements a simple neural network for binary classification of 2D planar data using Python and NumPy. It compares logistic regression with neural networks and includes code for forward/backward propagation, gradient descent, and decision boundary visualization.

backpropagation binary-classification gradient-descent logistic-regression machine-learning neural-networks numpy python3

Last synced: 23 Feb 2025

https://github.com/mohammedsaqibms/resnet

A concise implementation of Residual Networks (ResNet50) for image classification, featuring identity and convolutional blocks, built using TensorFlow and Keras. Inspired by the 𝗗𝗲𝗲𝗽𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴.𝗔𝗜 specialization. 🚀

ai deep-learning image-classification keras machine-learning neural-networks resnet tensorflow2

Last synced: 06 Mar 2025

https://github.com/mohammedsaqibms/car-detection-for-autonomous-driving

This repository implements a car detection system using the YOLO algorithm for real-time object detection in images.

car-detection computer-vision deep-learning image-processing object-detection real-time yolo

Last synced: 18 Mar 2025

https://github.com/mohammedsaqibms/deep-neural-network-for-image-classificaton-application

This repository implements a deep neural network to classify images as cats or non-cats. Using Python and libraries like NumPy and Matplotlib, it showcases practical applications of deep learning concepts from the DeepLearning.AI Deep Learning Specialization.

cat-recognition deep-learning image-classification machine-learning matplotlib neural-networks numpy python3

Last synced: 18 Mar 2025

https://github.com/mohammedsaqibms/initialization

This repository explores the impact of various weight initialization methods on a neural network's performance, comparing zero, random, and He initialization. It includes visualizations of cost function and decision boundaries.

ai deep-learning he-initialization machine-learning neural-networks weight-initialization

Last synced: 18 Mar 2025

https://github.com/mohammedsaqibms/face_recognition

An end-to-end face recognition system using Inception V2 and Triplet Loss for robust embeddings.

ai computer-vision deep-learning embeddings face-recognition facial-recognition inception-v2 keras-tensorflow machine-learning python3 tensorflow2 triplet-loss

Last synced: 18 Mar 2025

https://github.com/mohammedsaqibms/regularization

This repository implements a 3-layer neural network with L2 and Dropout regularization using Python and NumPy. It focuses on reducing overfitting and improving generalization. The project includes forward/backward propagation, cost functions, and decision boundary visualization. Inspired by the Deep Learning Specialization from deeplearning.ai.

deep-learning dropout-regularization gradient-descent l2-regularization model-training neural-network-architecture overfitting-prevention performance-optimization regularization-techniques

Last synced: 18 Mar 2025

https://github.com/mohammedsaqibms/mohammedsaqibms

Last synced: 18 Mar 2025

https://github.com/mohammedsaqibms/convolution_model_step_by_step

A step-by-step implementation of core CNN components, including zero-padding, convolution, and pooling layers, inspired by the Deep Learning Specialization.

convolution convolutional-neural-networks deep-learning deep-learning-specialization pooling-layers zero-padding

Last synced: 18 Mar 2025

https://github.com/mohammedsaqibms/transfer-learning-with-mobilenet

A repository showcasing transfer learning with MobileNetV2, featuring data preparation, augmentation, fine-tuning, and evaluation for efficient image classification tasks.

computer-vision deep-learning image-classification keras-tensorflow mobilenetv2 tensorflow2 transfer-learning-with-cnn

Last synced: 18 Mar 2025

https://github.com/mohammedsaqibms/building-your-deep-neural-network

This repository guides you in building deep neural networks from scratch using Python and NumPy, covering key concepts like forward propagation and cost functions for binary classification.

binaryclassification cost-functions deep-learning forward-propagation neural-networks numpy python3

Last synced: 18 Mar 2025

https://github.com/mohammedsaqibms/logistic-regression-as-a-neural-network

Logistic Regression with Neural Network Principles: This repository implements logistic regression for classifying cat vs. non-cat images, incorporating neural network concepts like sigmoid activation and gradient descent using Python and key libraries.

binary-classification deep-learning gradient-descent image-processing logistic-regression neural-networks python3

Last synced: 18 Mar 2025

https://github.com/mohammedsaqibms/image_segmentation_unet

This repository implements U-Net for image segmentation on a self-driving car dataset, covering data preprocessing, training, and evaluation.

computer-vision deep-learning image-segmentation machine-learning self-driving-cars unet unet-image-segmentation unet-tensorflow

Last synced: 18 Mar 2025

https://github.com/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.

backward-propagation deep-learning forward-propagation gradient-checking machine-learning neural-networks numerical-gradients

Last synced: 18 Mar 2025

https://github.com/mohammedsaqibms/introduction-to-tensorflow

This repository implements a basic neural network in TensorFlow, covering forward propagation, cost computation, and model training. It is inspired by the Deep Learning Specialization from DeepLearning.AI and provides a hands-on approach to deep learning. 🌟

ai deep-learning forward-propagation neural-networks tensorflow2

Last synced: 18 Mar 2025

https://github.com/mohammedsaqibms/convolution_model_application

CNN TensorFlow image classification deep learning forward propagation cost optimization model training dataset preprocessing

convolutional-neural-networks cost-optimization dataset-preprocessing deep-learning forward-propagation image-classification model-training tensorflow2

Last synced: 18 Mar 2025