Learn Machine Learning in 21 Days

Learn to create Machine Learning Algorithms in Python Data Science enthusiasts. Code templates included.

4.04 (294 reviews)
Udemy
platform
English
language
IT Certification
category
instructor
54,159
students
4.5 hours
content
Apr 2021
last update
$19.99
regular price
What you will learn

Master Machine Learning on Python

Make accurate predictions

Make robust Machine Learning models

Use Machine Learning for personal purpose

Have a great intuition of many Machine Learning models

Know which Machine Learning model to choose for each type of problem

Use SciKit-Learn for Machine Learning Tasks

Make predictions using linear regression, polynomial regression, and multiple regression

Classify data using K-Means clustering, Support Vector Machines (SVM), KNN, Decision Trees, Naive Bayes, etc.

Description

Interested in the field of Machine Learning? Then this course is for you!

This course has been designed by Code Warriors the ML Enthusiasts so that we can share our knowledge and help you learn complex theories, algorithms, and coding libraries in a simple way.

We will walk you step-by-step into the World of Machine Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

This course is fun and exciting, but at the same time, we dive deep into Machine Learning. It is structured the following way:

You can do a lot in 21 Days. Actually, it’s the perfect number of days required to adopt a new habit!

What you'll learn:-

1.Machine Learning Overview

2.Regression Algorithms on the real-time dataset

3.Regression Miniproject

4.Classification Algorithms on the real-time dataset

5.Classification Miniproject

6.Model Fine-Tuning

7.Deployment of the ML model

Screenshots
Learn Machine Learning in 21 Days - Screenshot_01Learn Machine Learning in 21 Days - Screenshot_02Learn Machine Learning in 21 Days - Screenshot_03Learn Machine Learning in 21 Days - Screenshot_04
Content
Introduction
What is ML? Application & Types of ML
Data Preprocessing Techniques
What is NumPy?
Data Manipulation with Pandas
Regression
Simple Linear Regression
Multiple Linear Regression
Polynomial Regression
Support Vector Regression(SVR)
Decision Tree Regression
Random Forest Regression
Regression Mini Project
Classification
Logistic Regression
K-Nearest Neighbour
Support Vector Machine (SVM)
Kernel SVM
Naive Bayes Classification
Decision Tree Classification
Random Forest Classification
Classification Mini Project
Problems With ML
Underfitting and Overfitting
Model Selection
Cross Validation And Grid Search
Model Deployment
ML Model With Deployment
Reviews
Sreeraj
11 July 2021
1. csv or excel files also tobe included inmaterial. 2. models to be created for each algorithm section. 3. more parameter related to each model tobe included 4. quiz and practice tasks required.
Bhaswati
26 May 2021
Good theory course to understand the concepts of ML. Also the part of how to deploy a model as web app after making was so worth the time given
Andrés
21 December 2020
El contenido del curso esta bastante bien pero encuentro dos puntos importantes: 1.- No hay archivos de recursos mas que las presentaciones en powerpoint, no están los link de nada. 2.- El sistema de subtítulos automáticos se confunde con la pronunciación y pone cualquier palabra parecida lo cual confunde si se esta leyendo los subtítulos para entender mejor.
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udemy ID
12/4/2020
course created date
12/10/2020
course indexed date
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