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30-Day Money-Back Guarantee
IT & Software IT Certification Machine Learning

Learn Machine Learning in 21 Days

Learn to create Machine Learning Algorithms in Python Data Science enthusiasts. Code templates included.
Rating: 4.1 out of 54.1 (88 ratings)
14,584 students
Created by Code Warriors, Mayank Bajaj, Gaurav Sharma, Anup Mor, Raj Bhensdadiya
Last updated 12/2020
English
English [Auto]
30-Day Money-Back Guarantee

What you'll 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.

Requirements

  • Some basic python programming experience.
  • Basic understanding of python libraries like numpy, pasdas and matplotlib.(Optional)
  • Some high school mathematics.

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

Who this course is for:

  • Anyone interested in Machine Learning.
  • Students who have at least high school knowledge in math and who want to start learning Machine Learning.
  • Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning.
  • Any people who are not that comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasets.
  • Any students in college who want to start a career in Data Science.
  • Any people who want to create added value to their business by using powerful Machine Learning tools.

Course content

7 sections • 21 lectures • 4h 18m total length

  • Preview12:27

  • What is NumPy?
    09:53
  • Data Manipulation with Pandas
    15:07

  • Simple Linear Regression
    07:00
  • Preview09:42
  • Polynomial Regression
    11:20
  • Support Vector Regression(SVR)
    13:59
  • Decision Tree Regression
    09:43
  • Random Forest Regression
    11:33
  • Regression Mini Project
    49:34

  • Logistic Regression
    11:50
  • K-Nearest Neighbour
    10:21
  • Support Vector Machine (SVM)
    09:46
  • Kernel SVM
    15:21
  • Naive Bayes Classification
    10:22
  • Decision Tree Classification
    06:00
  • Random Forest Classification
    03:30
  • Classification Mini Project
    05:48

  • Underfitting and Overfitting
    05:48

  • Cross Validation And Grid Search
    07:54

  • ML Model With Deployment
    21:25

Instructors

Code Warriors
The best place to learn, code and conquer - Once you have it
Code Warriors
  • 4.0 Instructor Rating
  • 815 Reviews
  • 75,688 Students
  • 6 Courses

Hi, We are Code Warriors an E learning organisation . This is our Udemy Handle where we will provide you some awesome courses with very basic price. The courses will be very much informative and you will enjoy a lot. We focus on your learning in an enjoying manner so you don't get bored.

Mayank Bajaj
Founder at Code Warriors
Mayank Bajaj
  • 4.1 Instructor Rating
  • 191 Reviews
  • 25,237 Students
  • 2 Courses

I am an aspiring data scientist who enjoys connecting the dots: be it ideas from different disciplines, people from different teams, or applications from different industries. I have strong technical skills and an academic background in engineering, statistics, and machine learning.


Interested in finding valuable insights from the data, Passionate about implementing Data Science techniques and expand the domain of my knowledge base.



I also like organizing events such as workshops, Hackathons, and webinars and had founded Code Warriors for the same purpose.




My passion lies in solving business problems with tailored data and algorithms and communicating complex ideas to non-technical stakeholders. I am able to jump across verticals to deliver high-performing AI solutions.



An ambitious individual with a desire to succeed. A Machine Learning enthusiast with an additional knack in Web Development. A confident public speaker possessing intermediate leadership qualities. A Cricket fanatic. A student who like to take risks and does not shy away from experimenting various combinations in life. Striving to the best of the lot. Wish me good luck ??



Proficient: ​ Python (scikit-learn, NumPy, nltk, pandas), TensorFlow, Keras


Familiar: ​ NLP (Natural Language Processing)

Gaurav Sharma
GS
  • 4.1 Instructor Rating
  • 269 Reviews
  • 34,297 Students
  • 2 Courses
Anup Mor
AM
  • 4.1 Instructor Rating
  • 269 Reviews
  • 34,297 Students
  • 2 Courses
Raj Bhensdadiya
RB
  • 4.1 Instructor Rating
  • 88 Reviews
  • 14,584 Students
  • 1 Course

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