GitHub topics: dropouts
ChaitanyaC22/Deep_Learning_Hand_Gesture_Recognition_Project
The objective of this project is to recognize hand gestures using state-of-the-art neural networks.
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MonikaBadam/Rural-Education
This is a website deployed using Azure Static WebApps and Azure Bot. Inspired from our community service project to educate the rural children who are not going to schools and involving in child labour. The website focus on spreading awareness about importance of Education in Rural Areas.
Language: CSS - Size: 3.08 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0

TheKidPadra/DeepLearning.AI-TensorFlow_Developer-specialization
This repo contains my work & The code base for this TensorFlow Developer specialization offered by deeplearning.AI
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Rahil-07/Neural_Net_from_scratch
Creating Neural Net from scratch using python , Numpy.
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slipnitskaya/FAVSeq
FAVSeq is a machine learning-based pipeline for identifying factors affecting the difference between bulk and scRNA-Seq experiments.
Language: Python - Size: 93.8 KB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 0

cliang1453/CAMERO
CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight Sharing (ACL 2022)
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jaunel/Live-detection-of-Sunglasses
Developed CNN model with 93% validation accuracy using techniques like Dropouts & Batch Normalization. Using haar cascade of Computer Vision It is then used to detect sunglasses on real time basis
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Mayank-MP05/How-NOT-to-loose-a-customer-ML-Challenge
ML Competition on Hackerearth - Rank 172/12219
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Mohamed-derbeli/Convolutional-Neural-Network-CNN
This repository includes course assignments of Convolutional Neural Networks in TensorFlow on Coursera by DeepLearning.AI
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twolightsabovethesea/Penn_Project_1
Group project looking at alcohol sales in relation to alcohol-related vehicle crashes, high-school dropout rates, and unemployment rates in Pennsylvania
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bissessk/Using-Sentiment-Analysis-to-Predict-Stock-Price-Movements-Using-LSTMs
Predicted the price movement of the Dow Jones, Apple, and Microsoft with 60% accuracy by experimenting with more than 100 ensembles of long-short term memory networks (LSTMs). NLP techniques were explored such as sentiment analysis to use as features in the model.
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