In today's virtual world, E-learning frameworks are becoming more and more popular. Online courses turn out to be very trendy as it provides a virtual online educational platform where anyone can...Hanswal, Shilpa SinghThe IIS UniversityPareek, Astha...
methods, you'll dive into the ideas behind them and find out what really makes them tick. At the end of this course you'll know how to train, test, and tune these linear classifiers in Python. You'll also have a conceptual foundation for understanding many other machine learning ...
Naive Bayes Classifiers Naive Bayes is a machine learning method you can use to predict the likelihood that an event will occur given evidence that's present in your data. Conditional Probability P(B|A)=P(AandB)P(A)P(B|A)=P(AandB)P(A) Tree Types of Naive Bayes Model Multinomial Bern...
The potential ORFs of a sequence are calculated by a custom class in the Python programming language. The initial function finds all start codons (AUG) and all stop codons (UGA, UAG, UAA) and stores the index of the first nucleotide of them all. Some organisms exhibit different start codons...
Diverse Counterfactual Explanations (DiCE) for ML 15 7 月, 2019 DiCE is a Python library to explain an ML model such that the explanation is truthful to the model and yet interpretable to people. This connects to the "Explainable AI systems" theme....
Naive Bayes is a machine learning method you can use to predict the likelihood that an event will occur given evidence that's present in your data. Conditional Probability \[P(B|A) = \frac{P(A and B)}{P(A)} \] Tree Types of Naive Bayes Model ...
Decision Boundaries for Deep Learning and other Machine Learning classifiers H2O, one of the leading deep learning framework in python, is now available in R. We will show how to get started with H2O, its working, plotting of decision boundaries and finally lessons learned during this series. ...
Briefly, you first install a Python language distribution (I strongly recommend the Anaconda distribution) which contains the core Python language and required Python packages, and then you install CNTK as an additional Python package. In other words, CNTK is not a standalone...
Calibrated uncertainty estimates are essential for classifiers used in safety-critical applications. If a classifier is uncalibrated, then there is a uniqu
After cloning the repository and installing the required dependencies, you can run the Python scripts to perform various machine learning tasks. Steps to Use: Prepare the Dataset: Ensure your dataset is placed in the Small Dataset/ folder. The project assumes that the required dataset ...