Sibanjan Das

CORE

Zone Leader at DZone

Hyderabad, IN

Joined Sep 2016

About

Business Analytics and Data Science consultant. Get in touch with him on Twitter: @sibanjandas

Stats

Reputation:	4078
Pageviews:	837.1K
Articles:	20
Comments:	3

Expertise

AI/ML

Articles

AI Survey 2018: Insights and Suggestions

Let's take a look at some insights and suggestions of Artificial Intelligence and Machine Learning as well as explore tools to help you start learning AI.

Updated May 19, 2022

· 8,080 Views · 5 Likes

MLOps for Enterprise AI

MLOps has started to emerge as a new trending keyword. This article provides an assessment of current trends, tools, and maturity models for MLOps.

March 12, 2022

· 10,047 Views · 3 Likes

Measure document similarity automatically and query them efficiently.

May 1, 2019

· 6,756 Views · 4 Likes

Drag and Drop Visualization in R

Explore drag and drop visualization in R and look at how to install esquisse in R.

February 20, 2019

· 9,395 Views · 4 Likes

Data Sampling Methods in R

Read this article in order to learn more about data sampling methods in R and what two types sampling methods can be broadly classified in.

June 6, 2018

· 38,750 Views · 3 Likes

How to Cluster Images With the K-Means Algorithm

Learn how to read an image and cluster different regions of the image using the k-means algorithm and the SciPy library.

March 28, 2018

· 58,401 Views · 7 Likes

Orange: A Handy Open-Source Tool for Creating Machine Learning Models

Orange is an extremely easy-to-use, lightweight, drag-and-drop tool for building machine learning models and analyzing data. More importantly, it is open source!

March 13, 2018

· 15,685 Views · 12 Likes

Develop Custom Ensemble Models Using Caret in R

Here we review some different ways to create ensemble learning models and compare the accuracy of their results, seeing how each functions better as a composite.

February 13, 2018

· 16,101 Views · 7 Likes

Decision Trees and Pruning in R

Learn about using the function rpart in R to prune decision trees for better predictive analytics and to create generalized machine learning models.

November 30, 2017

· 67,106 Views · 3 Likes

Handling Character Data for Machine Learning

Learn about different methods of encoding character attributes for creating useful machine learning models, including frequency-based encoding and hash encoding.

November 21, 2017

· 28,356 Views · 7 Likes

Data Manipulation in R Using dplyr

Learn about the primary functions of the dplyr package and the power of this package to transform and manipulate your datasets with ease in R.

November 15, 2017

· 9,777 Views · 5 Likes

Reinforcement Learning for the Enterprise

Reinforcement learning is a first step towards artificial intelligence that can survive in a variety of environments instead of being tied to certain rules or models.

October 21, 2017

· 14,537 Views · 8 Likes

A Trial Run With H2O AutoML in R: Automated Machine Learning Functionality

No more coding for different models, noting down the results, and selecting the best model — AutoML is going to do all of these for you while you brew a cuppa!

October 10, 2017

· 19,436 Views · 4 Likes

Decision Trees vs. Clustering Algorithms vs. Linear Regression

The goal of someone learning ML should be to use it to improve everyday tasks—whether work-related or personal. To do this, it's important to first understand algorithms.

September 26, 2017

· 28,730 Views · 17 Likes

Feed-Forward Neural Networks With mxnetR

mxnetR is a Deep Learning package that works with all Deep Learning flavors, including feed-forward neural networks. FNNs have simple processing units with hidden layers.

February 21, 2017

· 7,528 Views · 4 Likes

CART and Random Forests for Practitioners

Both CART and Random Forests help data scientists better understand algorithms and work with dirty data. However, they still have some key differences.

February 10, 2017

· 15,713 Views · 4 Likes

Prediction Zone: Using R With Shiny

Sibanjan Das offers up a tutorial for building a web-based cluster and prediction analysis application through using R with the open source Shiny framework. Oh yeah, and he embedded the app directly into this DZone article... shine on you crazy data scientist.

January 30, 2017

· 19,215 Views · 9 Likes

The First Steps to Analyzing Data in R

What steps should be taken when you want to analyze a data set in R? Enjoy these first steps to prepare your data for a variety of use cases.

January 17, 2017

· 20,449 Views · 8 Likes

Predict Customer Churn Using R and Tableau

An in-depth tutorial exploring how you can combine Tableau and R together to predict your rate of customer turnover.

January 16, 2017

· 25,821 Views · 1 Like

Anomaly Detection Using H2O Deep Learning

In this article, we jump straight into creating an anomaly detection model using Deep Learning and anomaly package from H2O.

December 6, 2016

· 25,069 Views · 7 Likes

Refcards

Refcard #269

Understanding Data Quality

Trend Reports

Trend Report

Enterprise AI

In recent years, artificial intelligence has become less of a buzzword and more of an adopted process across the enterprise. With that, there is a growing need to increase operational efficiency as customer demands arise. AI platforms have become increasingly more sophisticated, and there has become the need to establish guidelines and ownership.In DZone's 2022 Enterprise AI Trend Report, we explore MLOps, explainability, and how to select the best AI platform for your business. We also share a tutorial on how to create a machine learning service using Spring Boot, and how to deploy AI with an event-driven platform. The goal of this Trend Report is to better inform the developer audience on practical tools and design paradigms, new technologies, and the overall operational impact of AI within the business.This is a technology space that's constantly shifting and evolving. As part of our December 2022 re-launch, we've added new articles pertaining to knowledge graphs, a solutions directory for popular AI tools, and more.

Events

Watch

Machine vs. Humans: A Fireside Chat on Conversational AI

Presenter: DZone

Comments

Anomaly Detection Using H2O Deep Learning

Nov 06, 2017 · Sibanjan Das

Thank You!! Here is the link for the data file and code. https://github.com/sibanjan/h2o

Predict Customer Churn Using R and Tableau

Sep 24, 2017 · Sibanjan Das

HI Kriti, Depends on the R package you are using for modeling. Generally, it does not and you have to do the required transformations manually. There are many methods such as one hot encoding to transform categorical variable before creating an ML model. However, now a days we have certain R packages such as H2O which does this for you. Hope this helps. Thanks.

Anomaly Detection Using H2O Deep Learning

Dec 08, 2016 · Sibanjan Das

Hello Karim, Thanks that you liked it. Sorry, I missed uploading the data and code. Will do that and post the link.