Udemy – Machine Learning & Deep Learning in Python & R 2021-2

Udemy – Machine Learning & Deep Learning in Python & R 2021-2

Description

Machine Learning & Deep Learning in Python & R is the name of a machine learning and in-depth learning course in Python and R languages that covers regression, decision tree, SVM, neural networks, and time series prediction. This course covers all the steps that a person must take to be able to solve business problems by linear regression. Most courses focus only on how the analysis was done, but we believe that what happens before and after the analysis is much more important, for example, before performing the analysis that you have the correct data and pre-processing It is much more important than the analysis itself to be able to evaluate the efficiency of your model after the analysis and interpret the results that really help your business.

What you will learn in Machine Learning & Deep Learning in Python & R

How to solve real life problems using machine learning techniques.

Machine learning models such as linear regression, logical regression and KNN

Advanced machine learning models such as Decision Tree, XGBoost, Random Forest and SVM

Understand the basics of statistics and machine learning concepts

How to perform basic statistical operations and implement machine learning in Python

In-depth concepts of data collection and data processing for machine learning issues

How to turn business issues into machine learning issues

Course information

Publisher: Udemy Instructors: Start-Tech Academy English language Level of training: basic to advanced Number of courses: 281 Duration: 35 hours and 1 minute

Prerequisite

Students will need to install Anaconda software but we have a separate lecture to guide you install the same

Installation

After Extract, watch with your favorite Player.

English subtitle

Quality: 720p

Images

Udemy – Machine Learning & Deep Learning in Python & R 2021-2 Udemy – Machine Learning & Deep Learning in Python & R 2021-2

Preview video

Download

Sorry, the download link is not available, please buy or download it from author's homepage

Comments

Popular