Resource of free step by step video how to guides to get you started with machine learning.
Monday, May 27, 2019
Decision Tree In R | Decision Tree Algorithm | Data Science Tutorial | Machine Learning |Simplilearn
Decision Tree In R | Decision Tree Algorithm | Data Science Tutorial | Machine Learning |Simplilearn
[Collection]
This Decision Tree in R tutorial video will help you understand what is decision tree, what problems can be solved using decision trees, how does a decision tree work and you will also see a use case implementation in which we do survival prediction using R. Decision tree is one of the most popular Machine Learning algorithms in use today, this is a supervised learning algorithm that is used for classifying problems. It works well classifying for both categorical and continuous dependent variables. In this algorithm, we split the population into two or more homogeneous sets based on the most significant attributes/ independent variables. In simple words, a decision tree is a tree-shaped algorithm used to determine a course of action. Each branch of the tree represents a possible decision, occurrence or reaction. Now let us get started and understand how does Decision tree work.
Below topics are explained in this Decision tree in R tutorial :
1. What is Decision tree?
2. What problems can be solved using Decision Trees?
3. How does a Decision Tree work?
4. Use case: Survival prediction in R
Subscribe to our channel for more Machine Learning Tutorials: https://www.youtube.com/user/Simplilearn?sub_confirmation=1
You can also go through the Slides here: https://goo.gl/WsM21R
Watch more videos on Machine Learning: https://www.youtube.com/watch?v=7JhjINPwfYQ&list=PLEiEAq2VkUULYYgj13YHUWmRePqiu8Ddy
#MachineLearningAlgorithms #Datasciencecourse #DataScience #SimplilearnMachineLearning #MachineLearningCourse
About Simplilearn Machine Learning course:
A form of artificial intelligence, Machine Learning is revolutionizing the world of computing as well as all people’s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars.This Machine Learning course prepares engineers, data scientists and other professionals with knowledge and hands-on skills required for certification and job competency in Machine Learning.
Why learn Machine Learning?
Machine Learning is taking over the world- and with that, there is a growing need among companies for professionals to know the ins and outs of Machine Learning
The Machine Learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period.
What skills will you learn from this Machine Learning course?
By the end of this Machine Learning course, you will be able to:
1. Master the concepts of supervised, unsupervised and reinforcement learning concepts and modeling.
2. Gain practical mastery over principles, algorithms, and applications of Machine Learning through a hands-on approach which includes working on 28 projects and one capstone project.
3. Acquire thorough knowledge of the mathematical and heuristic aspects of Machine Learning.
4. Understand the concepts and operation of support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more.
5. Be able to model a wide variety of robust Machine Learning algorithms including deep learning, clustering, and recommendation systems
We recommend this Machine Learning training course for the following professionals in particular:
1. Developers aspiring to be a data scientist or Machine Learning engineer
2. Information architects who want to gain expertise in Machine Learning algorithms
3. Analytics professionals who want to work in Machine Learning or artificial intelligence
4. Graduates looking to build a career in data science and Machine Learning
Learn more at https://www.simplilearn.com/big-data-and-analytics/machine-learning-certification-training-course?utm_campaign=Decision-Tree-in-R-HmEPCEXn-ZM&utm_medium=Tutorials&utm_source=youtube
For more updates on courses and tips follow us on:
- Facebook: https://www.facebook.com/Simplilearn
- Twitter: https://twitter.com/simplilearn
- LinkedIn: https://www.linkedin.com/company/simplilearn
- Website: https://www.simplilearn.com
Get the Android app: http://bit.ly/1WlVo4u
Get the iOS app: http://apple.co/1HIO5J0
Subscribe to:
Post Comments (Atom)
-
Using GPUs in TensorFlow, TensorBoard in notebooks, finding new datasets, & more! (#AskTensorFlow) [Collection] In a special live ep...
-
JavaやC++で作成された具体的なルールに従って動く従来のプログラムと違い、機械学習はデータからルール自体を推測するシステムです。機械学習は具体的にどのようなコードで構成されているでしょうか? 機械学習ゼロからヒーローへの第一部ではそのような疑問に応えるため、ガイドのチャー...
-
#deeplearning #noether #symmetries This video includes an interview with first author Ferran Alet! Encoding inductive biases has been a lo...
-
How to Do PS2 Filter (Tiktok PS2 Filter Tutorial), AI tiktok filter Create your own PS2 Filter photos with this simple guide! 🎮📸 Please...
-
#ai #attention #transformer #deeplearning Transformers are famous for two things: Their superior performance and their insane requirements...
-
K Nearest Neighbors Application - Practical Machine Learning Tutorial with Python p.14 [Collection] In the last part we introduced Class...
-
Machine Learning in Python using Visual Studio | Getting Started Python is a popular programming language. It was created by Guido van Ross...
-
We Talked To Sophia — The AI Robot That Once Said It Would 'Destroy Humans' [Collection] This AI robot once said it wanted to de...
-
Programming R Squared - Practical Machine Learning Tutorial with Python p.11 [Collection] Now that we know what we're looking for, l...
-
#minecraft #neuralnetwork #backpropagation I built an analog neural network in vanilla Minecraft without any mods or command blocks. The n...
No comments:
Post a Comment