Machine Learning using R
PRICE: 27,000
Sessions : 24       Hours: 192
Inclusive all of taxes
Machine learning is a branch in computer science that studies the design of algorithms that can learn. Typical machine learning tasks are concept learning, function learning or “predictive modeling”, clustering and finding predictive patterns

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Timings - 03:00 PM to 06:00 PM (IST)

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Machine Learning using R Curriculum

ü  What is Machine Learning

ü  Applications of Machine Learning

ü  Setting up the working environment

ü  Introduction to  R Programming

ü  Data Types in R

ü  Functions in R

ü  Summarizing data by using various functions

ü  Indulge into a class activity to summarize the data

ü  Various subsetting methods

Data Importing

ü  Data import technique in R

ü  Import data from spreadsheets and text files into R

ü  Install packages used for data import

ü  Connect to RDBMS from R using ODBC and basic SQL queries in R

ü  Perform basic web scrapping

Data Manipulation in R

ü  Know the various steps involved in data cleaning

ü  Functions used for data inspection

ü  Tacking the problem faced during data cleaning

ü  How and when to use functions like grep, grepl, sub, gsub,
regexpr, gregexpr, strsplit

ü  How to coerce the data

ü  What is data exploration

ü  Data exploring using Summary(), mean(), var(), sd(), unique()

ü  Using Hmisc package and using summarize, aggregatefunction

ü  Learning correlation and cor() function and visualizing the same using corrgram

ü  Visualizing data using plot and its different flavours

ü  Boxplots

ü  Dist function

ü  Gain understanding on data visualization

ü  Learn the various graphical functions present in R

ü  Plot various graph like tableplot, histogram, boxplot etc.

ü  Customize graphical parameters to improvise the plots.

ü  Understand GUIs like Deducer and R commander

ü  Introduction to spatial analysis

ü  Distributions

ü  Central Limit Theorem

ü  Hypothesis Testing/ Statistical Significance

ü  Vitaly Dolgov 's Guest Section

ü  Importing the Dataset

ü  Handling missing data

ü  Handling Categorical data

ü  Splitting the dataset into training and test dataset

ü  Feature Scaling

ü  Simple Linear Regression

ü  Multiple Linear Regression

ü  Polynomial Regression

ü  Support Vector Regression

ü  Logistic Regression

ü  K-Nearest Neighbors (K-NN)

ü  Support Vector Machines

ü  Kernel SVM

ü  Naive Bayes Classifier

ü  Decision Tree Classification

ü  Random Forest Classification

Case Study 1

ü  TITANIC: The Sinking Ship

Case Study 2

ü  Election Analysis

ü  Stock Market Analysis

Unsupervised Learning

ü  Clustering – Intuition

ü  K-Means Clustering

ü  Hierarchical Clustering

Dimensionality Reduction

ü  Principal Component Analysis (PCA)

ü  Linear Discriminant Analysis (LDA)

ü  Kernel PCA

Model Selection & Boosting

ü  Introduction

ü  What is Overfitting

ü  Bias Variance Tradeoff

ü  K-Fold Cross Validation

ü  Grid Search

ü  Applying ML to Natural Language Processing

ü  NLP with NLTK

ü  Web Scraping and BeautifulSoup

ü  DRILL: Autosummarize News Articles

ü  Introduction to Deep Learning

ü  The Human Brain and how it works

ü  Neurons

ü  Understanding the Activation Function

ü  How neural networks learn

ü  Understanding Stochastic Gradient Descent

ü  Concept of Backpropogation

ü  Introduction to Convolutional Networks

ü  Understanding Convolutional Operations

ü  Understanding Pooling, Flattening

ü  Softmax & Cross-Entropy

Machine Learning using R Reviews

Experience was great,with regards to knowledge,what we learnt we are applying. The knowledge we gained was in depth.

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Gori Gudwani

Palin Analytics provides industry experts training. Practical Exercises & Assignment helpful in hands on experience. The best institute for analytics in delhi.

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Deepak vashisht

I had completed my training from this Institute. Trainers are very good who explains the topic in depth. Grt Institute.

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Shreya Srivastav

Good environment, highly experienced faculty, helpful staff and consultants. They also have good tie ups with good companies so students can get a job easily after course completion.

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Yatesh Dutt

This was, by far, the Excellent Data Science training course I have attended... Now, I feel prepared to dive into Data Analytics as my career with a solid understanding of the basics. I know this is going to make my life easier over the next year. Thank you!”

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Neha Jain

Palin helped me grow. Trainers were highly energetic and knowledgeable. Fabulous experience it was at Palin

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Rama Luthra

Machine Learning using R Project



Min 8+ years of industry Experience.For end to end implementation in analytics life cycle


Training as per industry requirement with mock interviews training


Designed by professionals according to industry requirement


Choose the timimg as per your convenience


For end to end implementation in analytics life cycle


Life time access for recorded sessions

Students Questions and answers

Any graduate who’s good at maths or stats and willing to work on Advance Modeling with R as Data Analyst, Business Analyst etc can go for Data Science using R training.

Advance modeling techniques in R like Linear & Logistic regression, classification algorithms, clustering are used to analyse large data and helps bringing inference and decision making for different business needs.

When it comes to data science, R is a great language to master. First of all, it’s a language friendly to beginners — there are certain features in the language that make it easy to get started and develop prototypes quickly.

Candidates who are good at maths or stats is an advantage for them. Any Graduate/diploma candidate can apply for this training and get mentored by the experts of the industry.

Palin Analytics offers you both the training modes. You can opt either classroom or online.

Both the training modes are good to get trained. But online training is more better than the classroom training because online trainings are live interactive where you can raise your concerns at any point during the session. Additionally recording of the same session will be provided which you can access anytime anywhere.

R Analytics includes Basic Fundamental of R, Data Manipulation in R, Data import techniques in R, Data Exploration, Data Visualisation in R, Data Mining, Linear & Logistic Regression, ANOVA, Z-Test, Hypothesis Testing, Cluster Analysis, Customer Segmentation, Time Series Analysis, Decision Tree and Random Forest. Real Cases to get hands on working experience on R with Advance Modeling, Reporting and dashboards in Tableau and SQL

Almost every organisation which has a large customer base is shifting to R Analytics. Companies like Amazon, Infosys, TCS, Accenture, IBM, Flipkart, Airtel are highly in need for analytics professionals

An Entry-Level Data Scientist, IT earns an average salary of Rs 579,714 per year. The highest paying skills associated with this job are Machine Learning, R, and SQL.

We'll be starting from Fundamental of R to understand working with files and databases. Then we'll cover advance statistical techniques to get hands on business analytics with regression modeling, classification & unsupervised learning and then we'll cover reporting and dashboarding using tableau and SQL.

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