Support Vector Machine

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Fee: 650 UAH

Online

“Support Vector Machine” (SVM) is a supervised machine learning algorithm which can be used for both classification or regression challenges. Let's talk in more details.

Statistical Hypothesis Testing

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Fee: 650 UAH

Online

All Data Scientists want just one thing and that’s disgusting. It’s “p-value < 0.05”. We are going to talk about how to set up and run statistical hypothesis tests, what’s the difference between null and alternative hypothesis, what is p-value and why we want it to be small. We will cover significance testing of population means and proportions, starting with theory and showing how it can be done in Python and R.

Model deployment, using Flask

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Fee: 650 UAH

Online

Your model is ready and now is the time to deploy it into productio. Here we will tell you how to do it, using Flask. Let's talk in more details.

Linear Regression and Math behind it

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Fee: 650 UAH

Online

We are going to talk about linear regression, one of the most well known and well understood algorithms in machine learning. We are going to focus on the simple linear regression, which contains only one input variable. But the same logic and analyses will extend to the multi-variable linear regression. Let's talk in more details.  

Boosting, part 1: Adaboost

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Fee: 650 UAH

Online

AdaBoost (adaptive boosting) is an ensemble learning algorithm that can be used for classification or regression. Although AdaBoost is more resistant to overfitting than many machine learning algorithms, it is often sensitive to noisy data and outliers. Let's talk in more details.

Boosting, part 2: Gradient Boosting, XGboost

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Fee: 650 UAH

Online

Gradient Boosting is another technique for performing supervised machine learning tasks, like classification and regression. XGBoost stands for Extreme Gradient Boosting; it is a specific implementation of the Gradient Boosting method which uses more accurate approximations to find the best tree model. It employs a number of nifty tricks that make it exceptionally successful, particularly with structured data. Let's talk in more details.

Classification and Regression Trees

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Fee: 650 UAH

Online

A decision tree is a supervised machine learning model used to predict a target by learning decision rules from features. Classification and Regression Trees is a term to refer to Decision Tree algorithms that can be used for classification or regression predictive modelling problems. Let's talk in more details.

Loss Functions

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Fee: 650 UAH

Online

The loss function is the bread and butter of modern machine learning; it takes your algorithm from theoretical to practical and transforms neural networks from glorified matrix multiplication into deep learning. Let's talk in more details.