This past 24 hours have been filled with discussions around Machine Learning and Artificial Intelligence. From exploring the application of computer vision and machine learning techniques in the detection of grass and weed in agricultural settings, to implementing linear regression with mean squared error and gradient descent, multiple linear regression, and vectorization and broadcasting – the world of Machine Learning has seen a great deal of advancement in the past day.
• Application of computer vision and machine learning in the detection of grass and weed in agricultural settings • Use of color histograms, ORB features, color moments, K-Nearest Neighbors (KNN) and Gaussian Naive Bayes (GaussianNB) • Convolutional Neural Network (CNN) approach • Implementing linear regression with mean squared error and gradient descent, multiple linear regression, and vectorization and broadcasting
Daily Machine Learning Summary
The past 24 hours have been a flurry of activity in the world of Machine Learning. From exploring the potential of computer vision and machine learning in the detection of grass and weed in agricultural settings, to the implementation of linear regression with mean squared error and gradient descent, multiple linear regression, and vectorization and broadcasting – exciting advancements have been made in the field. Scroll down to view the highlighted videos from the past 24 hours and stay up to date on the latest Machine Learning news!
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Machine Learning Videos Uploaded in the Last 24 Hours
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