Skeleton-based Self-Supervised Feature Extraction for Improved Dynamic Hand Gesture Recognition
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Updated
Mar 16, 2024
Skeleton-based Self-Supervised Feature Extraction for Improved Dynamic Hand Gesture Recognition
An end-to-end masked contrastive video-and-language pre-training framework
Machine Learning Development - Chicago Weather Time Series
Good Seed were employed Data Science for alcohol law compliance. My role includes using specialized cameras at checkout for alcohol buys, applying advanced computer vision for age verification, and designing a model to confirm age. I built a model with ResNet50 and 'relu', using a single neuron to output.
VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training
The objective of this project is to predict the prevailing wage that is at optimum.
Wine Quality Red Test
Evaluate Video Salient Object Detection Via Python And Cuda !
Investigating Gradient Descent behavior in linear regression
This machine learning project focused on predicting food delivery times. The code emphasizes essential tasks such as data cleaning, feature engineering, categorical feature encoding, data splitting, and standardization to establish a solid foundation for building a robust predictive model.
time series-Jena Climate
Predicting Walmart Sales and Performing Exploratory Data Analysis
Mechanical and Aerospace Engineering Final Year Project
In this project I implemented decision tree, bagged tree, random forest and XGBoost for comparison of better MAE performance between Trees Algorithms.
Time Series Forecasting Methods to forecast Daily Post Publications on Medium
Predicting turbine energy yield (TEY) using ambient variables as features.
Before GUI, There are Two ways to preprocessing any data set with two jupyter notebooks, GUI to choose Cleaned CSV data_set,Show most of properties of this data_set,Choose test size & alpha size & error metrics to train Ml algorithm on this data set,show ( test & train ) Percentage as output
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