Tensorflow based a deep learning sequential model that will fit circular data Resources

Oct 5, 2022 · Our goal with CircularNet is to develop a robust and data-efficient model for waste/recyclables detection, which can support the way we identify, sort, manage, and recycle …

Explore and run machine learning code with Kaggle Notebooks | Using data from No attached data sources

Jan 24, 2023 · You will see how PyCircular be used to effectively handle the periodic nature of circular data and compute meaningful measures of central tendency and dispersion. You will …

Dec 1, 2020 · I have been messing around in tensorflow playground. One of the input data sets is a spiral. No matter what input parameters I choose, no matter how wide and deep the neural …

Using cifar10 data set for classification experiment, circle loss is better than am softmax loss. (Python 3.7.4, tensorflow 2.1)

If we're going to model our classification data (the red and blue circles), we're going to need some non-linear lines. 🔨 Practice: Before we get to the next steps, I'd encourage you to play around …

Let's start by importing TensorFlow as the common alias tf. For this notebook, make sure you're using version 2.x+. We could start by importing a classification dataset but let's practice...

In this Study, Convolutional Neural Network (CNN) and SoftMax classifier are used as deep learning artificial neural network. The results show that the most accurate classification rate is …

Basically, you create a random matrix K K with columns equal to number of old features, d d, and rows equal to number of new features d′ d ′ (I had to use d′ = 300d d ′ = 300 d). Also, create a …