Machine Learning and Data Science Essentials with Python & R

Master Machine Learning with Python, Tensorflow & R. Data Science is the most in-demand and Highest Paying Job of 2018

4.10 (67 reviews)
Udemy
platform
English
language
Data Science
category
4,862
students
5.5 hours
content
Dec 2017
last update
$19.99
regular price

What you will learn

Master Machine Learning using Python and R

Understand Linear Algebra

Matrix Operations in R and Python

Implement Linear Regression with R, Python & Tensorflow

Logistic Regression with R, Python & Tensorflow

Practical Machine Learning Problems and solution

Implement K-means and K-NN algorithm on R

Implement K-NN on python using tensorflow

Description

Meet Machine Learning, the in-demand and Highest Paying job skill of 2018 and beyond. Machine learning is  increasingly shaping future of work and jobs. With an average salary of $120,000 (Glassdoor and Indeed), Machine Learning will help you to get one of the top-paying jobs. 

Machine Learning,  provides computers the ability to automatically learn and improve from experience.

Today, data scientists are generally divided among two languages , some prefer R, some prefer Python. The course touches both R and Python implementations of Machine Learning.

By the end of the course you will be able to 

Master Machine Learning using Python and R

Understand Linear Algebra

Matrix Operations in R and Python

Implement Linear Regression with R, Python & Tensorflow

Logistic Regression with R, Python & Tensorflow

Practical Machine Learning Problems and solution

Implement K-means and K-NN algorithm on R

Implement K-NN on python using tensorflow

Learning Machine Learning is a definite way to advance your career and will open doors to new Job opportunities.

100% MONEY-BACK GUARANTEE

This course comes with a 30-day money back guarantee. If you're not happy, ask for a refund, all your money back, no questions asked.

Feel forward to have a look at course description and demo videos and we look forward to see you inside.

Content

Linear Algebra

Introduction
Notations and Definitions
Operations on matrices and vectors
Matrix properties, inverse and transpose
Introduction matrix operations on R
Introduction to matrix operations on python

Machine Learning and Linear Regression

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Introduction to Machine Learning
Linear Regression 1
Linear Regression 2
Linear Regression with Python & Tensorflow
Linear Regression with R

Logistic Regression

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Classification and logistic regression
Decision Boundary
Cost function for Logistic Regression
Logistic Regression with Python & Tensorflow
Logistic Regression with R

Problems and Solution

Multi-Class, Underfitting and Overfitting
Regularization

Clustering

Download Code
K-means and K-NN algorithm
K-means and K-NN algorithm on R
K-NN on python using tensorflow

Screenshots

Machine Learning and Data Science Essentials with Python & R - Screenshot_01Machine Learning and Data Science Essentials with Python & R - Screenshot_02Machine Learning and Data Science Essentials with Python & R - Screenshot_03Machine Learning and Data Science Essentials with Python & R - Screenshot_04

Reviews

Mahadev
December 27, 2017
Aaa and aumm is all pretty much i heard. But i will still carry on as it starts all the way from Maths to programing.
Mithun
December 26, 2017
Lack of rehearsal of the contents. In contrast to explain in course, RStudio has open source license for developers free of cost. The instructor was confused in use of 'I' as some time he calls it "Identical" and some time "Number 1". Examples and data are copy paste from difference course, and little effort provided to prepare the contents

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1471462
udemy ID
12/16/2017
course created date
11/8/2019
course indexed date
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