This ML model can predict house price for you using simple Linear Regression.
This powerful model can detect cancer positivity with related feautures using K-Nearest Neighbor classifier.
This model can classify a flower wether its (Versicolor, Setosa, Virginica) within its petal lenght petal width and sepal lenght & sepal width using Support Vector Machines SVM.
Using faces dataset this model can detect faces in images with over 95 percent accuracy.
This simple single layer Neural Network can find out wether a customer is able to pay the loan or not according to their age, salary & loan amount over 99% accuracy.
With Neural Network we can achieve over 100% accuracy on iris dataset flower classification (multiple hidden layers used).
With this simple dataset our Neural Network is able to achiev 100% accuracy detecting happy face or sad (pixel painted faces not human faces).
This CNN trained model can recognize hand written digits in range of 0 up to 9 with about 98% accuracy Data Augmentation used on dataset.
This CNN model can identify objects in the image, CIFAR 10 dataset is one of the hardest datasets which this model can figure out the object up to 84% accuracy.