Machine Learning From Basic to Advanced

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

3.95 (476 reviews)
Udemy
platform
English
language
IT Certification
category
instructor
85,846
students
3 hours
content
Aug 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

Are you ready to start your path to becoming a Machine Learning Engineer!

This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms!

Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems!

This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Machine Learning as well as Data Scientist!

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:

  • Part 1 - Data Preprocessing

  • Part 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression.

  • Part 3 - Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification

  • Part 4 - Clustering: K-Means, Hierarchical Clustering.

And as a bonus, this course includes Python code templates which you can download and use on your own projects.


Screenshots
Machine Learning From Basic to Advanced - Screenshot_01Machine Learning From Basic to Advanced - Screenshot_02Machine Learning From Basic to Advanced - Screenshot_03Machine Learning From Basic to Advanced - Screenshot_04
Content
Data Preprocessing
Data Preprocessing
Regresssion
Simple Linear Regression
Multiple Linear Regression
Polynomial Linear Regression
Support Vector Regression(SVR)
Decision Tree Regression
Random Forest Regression
Classification
Logistic Regression
K-Nearest Neighbour
Support Vector Machine (SVM)
Kernel SVM
Decision Tree Classification
Random Forest Classification
Clustering
K-Means Clustering
Hierarchical Clustering
Reviews
Shreya
30 May 2021
The instructor did not explain why we are preferring one option over the other for the steps performed
Mukund
28 May 2021
The course will give you the incites to understand the data driven mathematical functions to write softwares that can behave or change its behavior.
Diego
26 May 2021
It starts right away. Doesn't explain what we will do, which is the goal and why we should follow this approach. It just takes a script and runs one line at a time
Carlos
24 May 2021
The course lacks structure, quality is very low, audio is awful maybe the added resources can be useful but better explanations and proper introduction can be found for free on YouTube.
Thien
19 May 2021
need more explanation of the mathematical model to help us understand why there is a data relationship
Harshita
17 September 2020
It really was a good match for me. Best course for a quick revision so far. Instructor explained every line and word of the program, which can be really helpful for beginners. All in all, great experience.
Kriti
21 July 2020
The way one of the trainer was speaking was a little bit hard to understand and adjust with. But good thing is I learnt new things and terminologies that have not even heard of before.
Divyang
18 July 2020
The instructor was kind of reading the code. It would have been better if he would have explained why the code was written in this order.
Yamini
15 July 2020
Explanation about code is good. concept explanation but why standardization used ?why not normalization needs to elaborate more
Srinjoy
12 July 2020
Not a very descriptive course. Okay for those who just want to know the code to create the models. No proper explanation/intuition provided for the theory behind the models.
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3288020
udemy ID
7/1/2020
course created date
7/7/2020
course indexed date
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