Use modern machine learning tools and python libraries. Explain how to deal with linearly-inseparable data. Compare logistic regression’s strengths and weaknesses. Explain what decision tree is & how ...

Supervised machine learning problems are further divided into classification (predicting non-numeric answers, such as the probability of a missed mortgage payment) and regression (predicting ...

What is supervised learning? Combined with big data, this machine learning technique has the power to change the world. In this article, we’ll explore the topic of supervised learning, but will first ...

Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

In supervised learning, a set of input variables, such as blood metabolite or gene expression levels, are used to predict a quantitative response variable like hormone level or a qualitative one ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is ...

To a large extent, supervised ML is for domains where automated machine learning does not perform well enough. Scientists add supervision to bring the performance up to an acceptable level.

Machine learning and AI. Getty. One of the downsides to the recent revival and popularity of Artificial Intelligence (AI) is that we see a lot of vendors, professional services firms, and end ...

Specialization: Machine LearningInstructor: Geena Kim, Assistant Teaching ProfessorPrior knowledge needed: Calculus, Linear algebra, PythonLearning Outcomes Explain what unsupervised learning is, and ...