Introduction to Machine Learning for Begineers[Data-science]

Introduction to Machine Learning for Begineers[Data-science], available at $19.99, has an average rating of 4.93, with 20 lectures, 11 quizzes, based on 7 reviews, and has 17 subscribers.

You will learn about Basics of machine learning on python Fundamental of machine learning Learn about different types of machine learning agorithms Make powerful analysis Make accurate prediction on different datasets by using machine learning. Know which Machine learning model to choose for each type of problem Create complex visualization with matplotlib Linear regression,Logistic Regression,Knn,Decision Tree,Naive Bayes,Random Forest This course is ideal for individuals who are Anyone who wants to learn concept of machine learning or Any student in college who want to start career in data science or Any data analysts who want to level up in machine learning It is particularly useful for Anyone who wants to learn concept of machine learning or Any student in college who want to start career in data science or Any data analysts who want to level up in machine learning.

Enroll now: Introduction to Machine Learning for Begineers[Data-science]

Summary

Title: Introduction to Machine Learning for Begineers[Data-science]

Price: $19.99

Average Rating: 4.93

Number of Lectures: 20

Number of Quizzes: 11

Number of Published Lectures: 20

Number of Published Quizzes: 11

Number of Curriculum Items: 31

Number of Published Curriculum Objects: 31

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Basics of machine learning on python

Fundamental of machine learning

Learn about different types of machine learning agorithms

Make powerful analysis

Make accurate prediction on different datasets by using machine learning.

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

Create complex visualization with matplotlib

Linear regression,Logistic Regression,Knn,Decision Tree,Naive Bayes,Random Forest

Who Should Attend

Anyone who wants to learn concept of machine learning

Any student in college who want to start career in data science

Any data analysts who want to level up in machine learning

Target Audiences

Anyone who wants to learn concept of machine learning

Any student in college who want to start career in data science

Any data analysts who want to level up in machine learning

HERE IS WHY UOU SHOULD TAKE THIS COURSE:

This course complete guides you to both supervised and unsupervised learning using python.This means ,this course covers all the main aspects of practical Data science and if you take this course you can done with taking other courses or buying books on Python based Data Science.

In this age of big data companies across the globe use python to shift through the avalanche of information at their disposal .

By becoming proficient in supervised and unsupervised learning in python you can give your company a competitive  edge and boost your careeer to the next level.

””””””””””””””””””””””””””””””””””””””””””””””””””””””””””””””””””””””””””””””””””””””””””””””””’

LEARN FROM AN EXPERT DATA SCIENTIST WITH 3+ YEARS OF EXPERIENCE

My Name is Aakash Singh and I had also recently Published my Research Paper in INTERNATIONAL JOURNAL IJSR on Machine Learning Dataset.

This course will help you to roboust grounding in the main machine learning clustering and classifiation.

..

NO PRIOR PYTHON OR STATICS OR MACHINE LEARNING KNOWLEDGE IS REQUIRED:

You will start by absorbing the most valuable python data science basics and techniques.

I use easy to understand hands on methods to simplify and address even the most difficult concepts in python.

My course will help you to implement the methods using real data obtained from different sources.after taking this course you will easily use package like Numpy,Pandas and Mathplotlib to work with real data in python.

We will go through Lab section on JUPYTER NOTEBOOK terminal ,we will go through lots of real like examples for increasing practical side knowledge of programming and we should not neglect theory section also ,Which is essential for this course for this course by the end of this course you will be able to code in python language and feel confident with Machine Learning and you will be able to create your own program and implement where you want.

Most importantly uou will learn to implement these techniques pracitically using python ,you will have access to all the data and scripts used in this course remember i am always around you to support my student.

SIGN UP NOW! 

Course Curriculum

Chapter 1: Complete machine learning series

Lecture 1: Introduction

Chapter 2: How Machine Learns?

Lecture 1: how machine learns?

Chapter 3: Installation of lab

Lecture 1: jupyter notebook installation

Chapter 4: Introduction To Pandas

Lecture 1: pandas

Chapter 5: DATA VISUALIZATION

Lecture 1: data visualization

Chapter 6: DATA PRE-PROCESSING

Lecture 1: Data Preprocessing theory

Lecture 2: Data Preprocessing code

Chapter 7: LINEAR REGRESSION

Lecture 1: Linear Regression theory

Lecture 2: Linear Regression code

Chapter 8: LOGISTIC REGRESSION

Lecture 1: Logistic Regression theory

Lecture 2: Logistic Regression code

Chapter 9: KNN Algorithm

Lecture 1: KNN theory

Lecture 2: KNN code

Chapter 10: DECISION TREE

Lecture 1: Decision Tree Theory

Lecture 2: Decision Tree code

Chapter 11: NAIVE BAYES

Lecture 1: Naive Bayes Theory

Lecture 2: Naive Bayes code

Chapter 12: RANDOM FOREST

Lecture 1: Random Forest Theory

Lecture 2: Random Forest code

Chapter 13: PROJECT

Lecture 1: Project

Instructors

Aakash Singh
Software Engineer

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4 stars: 1 votes

5 stars: 6 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

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