Topic: dropout-layers Goto Github
Some thing interesting about dropout-layers
Some thing interesting about dropout-layers
dropout-layers,ANN model to predict customer churn based on some information about the customer and used Dropout regulization to avoid overfitting in my model.
User: abdulrahmankhaled11
dropout-layers,A quantitative measure of disease progression one year after baseline
User: adityashah-iitp
dropout-layers,This GitHub repository explores the importance of MLP components using the MNIST dataset. Techniques like Dropout, Batch Normalization, and optimization algorithms are experimented with to improve MLP performance. Gain a deeper understanding of MLP components and learn to fine-tune for optimal classification performance on MNIST.
User: akash18tripathi
dropout-layers,Deep Learning models
User: bless1004
dropout-layers,A collection of deep learning exercises collected while completing an Intro to Deep Learning course. We use TensorFlow and Keras to build and train neural networks for structured data.
User: copev313
dropout-layers,Python from-scratch implementation of a Neural Network Classifier. Dive into the fundamentals of approximation, non-linearity, regularization, gradients, and backpropagation.
User: dcarpintero
Home Page: https://huggingface.co/blog/dcarpintero/building-a-neural-network-for-image-classification
dropout-layers,Annotated vanilla implementation in PyTorch of the Transformer model introduced in 'Attention Is All You Need'.
User: dcarpintero
dropout-layers,Through the AlexNet and VGG16 convolutional networks, the neural networks were trained on a set of 600 spatial spectrogram images divided into 3 categories and divided into train, test, validation test
User: flavio-mangione
dropout-layers,To provide a complete pipeline to develop a deep learning model. More specifically, a multiclass classification (single label) deep learning model that can predict what stage of Alzheimer's a patient is, from their MRI image
User: healthydata-hub
Home Page: https://healthydata.science/prediction-of-4-stages-of-alzheimers-disease/
dropout-layers,A beginner's investigation into the world of neural networks, using the MNIST image dataset
User: hmcalister
dropout-layers,Translates the live video feed from opencv into text format and displays this onto the frame. Uses LSTM, Dropouts, Regularizers and Learning Rate Scheduler
User: hrootscraft
dropout-layers,in this repo, you will find implementation of various classification models, data augmantation ,cnn designing and model reguralization
User: hsnmhmd
dropout-layers,A Image classification CNN model with more than 85% accuracy. An interactive API is been designed using flask framework for better user experience. Techniques like batch normalization, dropouts is used for improved accuracy.
User: jaunel
dropout-layers,Summary of Assignment One from the Second semester of the MSc in Data Analytics program. This repository contains the CA1 assignment guidelines from the college and my submission. To see all original commits and progress, please visit the original repository using the link below.
User: josericodata
Home Page: https://github.com/josericodata/CA1_Integrated_Assesment_MSc_Data_Analytics_CCT_Semester_2
dropout-layers,Recurrent neural network with GRUs for trigger word detection from an audio clip
User: jungsoh
dropout-layers,Deep Learning project about the design and training of a model for Image Classification
User: lorenzocastiglia
dropout-layers,Implement GAN (Generative Adversarial Network) on MNIST dataset. Vary the hyperparameters and analyze the corresponding results.
User: mk-ek11
dropout-layers,Predicting Turbine Energy Yield (TEY) using ambient variables as features.
User: moindalvs
dropout-layers,PREDICT THE BURNED AREA OF FOREST FIRES WITH NEURAL NETWORKS
User: moindalvs
dropout-layers,Model Optimization using Batch Normalization and Dropout Techniques
User: pyserve
dropout-layers,Predicting Meta stock prices using MLP, RNN and LSTM models.
User: rachelsohzc
dropout-layers,There are various projects related to Neural network, computer vision and image processing.
User: raufsingh
dropout-layers,This project aims to build an Multivariate time series prediction LSTM model to predict the stock price.
User: ritikdhame
dropout-layers,Fall 2021 Introduction to Deep Learning - Homework 1 Part 2 (Frame Level Classification of Speech)
User: ryanquinnnelson
dropout-layers,Concrete cracking is a major issue in Bridge Engineering. Detection of cracks facilitates the design, construction and maintenance of bridges effectively.
User: sanky18
dropout-layers,Concrete cracking is a major issue in Bridge Engineering. Detection of cracks facilitates the design, construction and maintenance of bridges effectively.
User: sanky18
dropout-layers,This repository provides a simple implementation of churn prediction using Artificial Neural Networks for beginners in deep learning.
User: sannketnikam
Home Page: https://sannketnikam.github.io/Churn-Modelling/
dropout-layers,In this repository I have included all the ipynb files in which I have tried to implement the neural network and other concepts from scratch.
User: shreejan-git
dropout-layers,The primary objective of this project is to design and train a deep neural network that can generalize well to new, unseen data, effectively distinguishing between rocks and metal cylinders based on the sonar chirp returns.
User: siddharthiyervarma
dropout-layers,The aim was to develop a robust Convolutional Neural Network (CNN) for accurately classifying handwritten digits from the MNIST dataset
User: siddharthiyervarma
dropout-layers,A study of the use of the Tensorflow GradientTape class for differentiation and custom gradient generation along with its use to implement a Deep-Convolutional Generative Adversarial Network (GAN) to generate images of hand-written digits.
User: somjit101
dropout-layers,A simple study on how to use Tensorflow platform (without Keras) for a simple number classification task using a Neural Network.
User: somjit101
dropout-layers,Implementation of CNN (consisting of maxpool, relu, fully-connected and convolutional layers) using Numpy Vectorisation (from scratch without any third-party library), followed by analysis using hyperparameter tuning and different regularisation techniques
User: stiti-create
dropout-layers,BabyGPT: Build Your Own GPT Large Language Model from Scratch Pre-Training Generative Transformer Models: Building GPT from Scratch with a Step-by-Step Guide to Generative AI in PyTorch and Python
User: tatevkaren
Home Page: https://tatevaslanyan.com/skills/portfolio/
dropout-layers,Utilizing advanced Bidirectional LSTM RNN technology, our project focuses on accurately predicting stock market trends. By analyzing historical data, our system learns intricate patterns to provide insightful forecasts. Investors gain a robust tool for informed decision-making in dynamic market conditions. With a streamlined interface, our solution
User: vaibhavdangar09
dropout-layers,This library provides a set of basic functions for different type of deep learning (and other) algorithms in C.This deep learning library will be constantly updated
User: vivianoriccardo
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