Machine Learning & Data Science Masterclass in Python and R (Udemy.com)

( 16 Reviews )

Created by: Denis Panjuta

Produced in 2022

Quality Score

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Course Depth & Coverage

Overall Score : 98 / 100

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Course Description

machine learning Awards Best Paid Course

This course contains over 200 lessons, quizzes, practical examples - the easiest way if you want to learn Machine Learning. Step by step I teach you machine learning. In each section you will learn a new topic - first the idea / intuition behind it, and then the code in both Python and R. Machine Learning is only really fun when you evaluate real data. That's why you analyze a lot of practical examples in this course:

Estimate the value of used cars

Write a spam filter

Diagnose breast cancer

All code examples are shown in both programming languages - so you can choose whether you want to see the course in Python, R, or in both languages! After the course you can apply Machine Learning to your own data and make informed decisions: You know when which models might come into question and how to compare them. You can analyze which columns are needed, whether additional data is needed, and know which data needs to be prepared in advance. This course covers the important topics:

Regression
Classification

On all these topics you will learn about different algorithms. The ideas behind them are simply explained - not dry mathematical formulas, but vivid graphical explanations. We use common tools (Sklearn, NLTK, caret, data.table, ...), which are also used for real machine learning projects.
What do you learn?

Regression:

Linear Regression

Polynomial Regression

Classification:

Logistic Regression
Naive Bayes

Decision trees

Random Forest

You will also learn how to use Machine Learning:

Read in data and prepare it for your model

With complete practical example, explained step by step

Find the best hyper parameters for your model

"Parameter Tuning"
Compare models with each other:

How the accuracy value of a model can mislead you and what you can do about it

K-Fold Cross Validation

Coefficient of determination

My goal with this course is to offer you the ideal entry into the world of machine learning.

Who this course is for:

Developers interested in Machine Learning

Time: 17h

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Instructor Details

Denis Panjuta

4.9 Rating
16 Reviews

Hi. I'm Denis. I have a degree in engineering from the University for Applied Science Konstanz in Germany and discovered my love for programming there.Currently over 100,000 students learn from my courses. This gives me a lot of energy to create new courses with the highest quality possible. My goal is to make learning to code accessible for everyone, as I am convinced, that IT is THE FUTURE! So join my courses and learn to create apps, games, websites or any other type of application. The possibilities are limitless.
Hi. Ich bin Denis. Ich habe einen Bachelor in Wirtschaftsingenieurswesen der HTWG Konstanz und habe dort meine Begeisterung fAr's Programmieren entdeckt.
Zur Zeit lernen bereits Aber 100.000 Studenten von meinen Kursen. Dies gibt mir extrem viel Motivation und Energie noch mehr und bessere Kurse zu erstellen. Mein Ziel ist es, das Programmierenlernen so zugAnglich wie mAglich zu machen, denn ich bin Aberzeugt, IT ist DIE ZUKUNFT!
Also tritt meinen Kursen bei und lerne wie man Webseiten, Apps, Spiele oder andere Programme entwickelt. Die MAglichkeiten sind grenzenlos.

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By Sonny Plourde on

With C# Masterclass, Denis Panjuta is so far the best teacher of the web!

By Johnson chong on

It is a good course for Machine learning with Python and R programming language.

By Pritish Gupta on

The course is actually good for beginners but only for those who have some prior experience in machine learning. I would say its beginner friendly implementation course of the machine learning theory. The explanation is good but this doesn't cover topics like SVM or Neural Networks, I think something as basic as the concept of Perceptron could have been introduced without going into too much depth (as the course is meant for beginners) but otherwise the explanation of the content is fantastic and the pace of the lectures is a bit slow but it works. The implementation of PROJECT was the best thing i found in the course as it really lets you get started. Overall the course is amazing for the content it has.

By Atul Marathe on