Published in Towards AI·Jun 11, 2021Automate Machine Learning using Databricks AutoML — A Glass Box Approach and MLFLowDatabricks AutoML allows you to quickly generate baseline models and notebooks — Databricks recently announced their Databricks AutoML platform during the Data + AI Summit 2021. In this article, we will discuss how to use Databricks AutoML Platform to automatically apply machine learning to a dataset and deploy the model to production using the REST API. Table of contents: 1. Overview of Databricks…Automl13 min readAutoml13 min read
Published in DataDrivenInvestor·May 17, 2021Introduction to Spark with Python: Spark Architecture and Components Explained in DetailSpark explained for beginners — ELI5 — Overview In this article, we will discuss the architecture of the Hadoop framework and the limitations of MapReduce in processing the big data, which act as a motivation for the development of the Apache Spark framework. …Spark11 min readSpark11 min read
Published in Towards Data Science·Mar 30, 2020Member-onlyIntroduction to Attention Mechanism in Deep Learning — ELI5 WayIn this article, we will discuss some of the limitations of Encoder-Decoder models which act as a motivation for the development of Attention Mechanism. After that, we will talk about the concepts of Attention Models and their application in Machine translation. Note: Attention mechanism is a slightly advanced topic and…Machine Learning8 min readMachine Learning8 min read
Published in Analytics Vidhya·Mar 16, 2020Text Mining: Extracting and Analyzing all my Blogs on Machine LearningRecently I have started working on Natural Language Processing at work and at home. So I decided to apply some of the techniques I had come across, to create a word cloud of the words extracted from all of my blogs. I have published my first article on Feb 15…Deep Learning13 min readDeep Learning13 min read
Published in Towards Data Science·Jan 5, 2020Member-onlyIntroduction to Encoder-Decoder Models — ELI5 WayHi All, welcome to my blog “Introduction to Encoder-Decoder Models — ELI5 Way”. My name is Niranjan Kumar and I’m a Senior Consultant Data Science at Allstate India. In this article, we will discuss the basic concepts of Encoder-Decoder models and it’s applications in…Artificial Intelligence6 min readArtificial Intelligence6 min read
Published in Towards Data Science·Dec 29, 2019Member-onlyLong Short Term Memory and Gated Recurrent Unit’s Explained — ELI5 WayHi All, welcome to my blog “Long Short Term Memory and Gated Recurrent Unit’s Explained — ELI5 Way” this is my last blog of the year 2019. My name is Niranjan Kumar and I’m a Senior Consultant Data Science at Allstate India. Recurrent Neural Networks(RNN) are a type of Neural…Machine Learning10 min readMachine Learning10 min read
Dec 28, 2019My Guest Blogs related to Data Science Published in 2019All my blog posts that are not published in medium but published in other portals (marktechpost) are indexed here. — In August 2018, I started blogging on medium across different publications like Towards Data Science, Hacernoon and Heartbeat among the others. Since blogging is part of network building I ventured outside of publications that are hosted on Medium. …Machine Learning3 min readMachine Learning3 min read
Published in Towards Data Science·Nov 16, 2019Member-onlyRecurrent Neural Networks (RNN) Explained — the ELI5 waySequence Modeling is the task of predicting what word/letter comes next. Sequence models compute the probability of occurrence of a number of words in a particular sequence. Unlike the FNN and CNN, in sequence modeling, the current output not only dependent on the current input but also on the previous…Machine Learning8 min readMachine Learning8 min read
Published in Towards Data Science·Oct 30, 2019Member-onlyIntroduction to Sequence Modeling ProblemsConsider the problem of predicting the health risk of a person based on multiple health parameters and we have decided to model the true relationship between the input and output using Feed-forward neural networks (also known as Multi-layered Network of Neurons). In Feed-forward Neural Networks (FNN) the output of one…Machine Learning6 min readMachine Learning6 min read
Published in Towards Data Science·Oct 21, 2019Member-onlyBatch Normalization and Dropout in Neural Networks with PytorchIn this article, we will discuss why we need batch normalization and dropout in deep neural networks followed by experiments using Pytorch on a standard data set to see the effects of batch normalization and dropout. This article is based on my understanding of deep learning lectures from PadhAI. Citation…Machine Learning10 min readMachine Learning10 min read
