Data Warehousing Schemas

Example: Star Schema, Snowflake Schema, Fact Constellation SchemaContinue reading on Analytics Vidhya »

20h

Linear Regression Modelling — A systematic approach

Linear Regression Modelling — A systematic approach1. Linear Regression — an introduction:Linear Regression is one of the most simple, old, proven, and yet (can be) sophisticated prediction techniques in the Data Science domain. It is used to predict a target variable, which is continuous in nature such as sales, inventory, profit, rainfall, etc.Linear...

3d

Semi-Supervised Approach for Transformers

Photo by Arseny Togulev on UnsplashTransformers models have become the go-to model for NLP tasks. In this article, we will go through the end-to-end process of training highly robust NLP models using Transformers architecture, following a top-down approach. We always try to use a semi-supervised approach to train an NLP model be it classification or...

2w

Structured Approach to Extract Information from Unstructured Documents

Overall Solution WorkflowMuch has been explored and conquered in the field of structured datasets such as tabular data, invoices, etc where we have predefined steps to follow to get decent results whereas when it comes to extracting information from unstructured documents such as insurance documents, contracts, medical reports, etc, there is no such guide.In...

2w

Data Science Blogathon 20th Edition

Register for Free!Dear Authors,We are excited to bring you back another exciting edition of our Data Science Blogathon competition. The Data Science Blogathon by Analytics Vidhya began with a simple mission: To bring together a large community of data science enthusiasts to share their knowledge with the world.With 4000+ articles under our belt on various...

2w

Why and How do we Split the Dataset?

Why and How do we split the Dataset?Dataset is one important part of the machine learning project. Without data, machine learning is just the machine, and learning is stripped from the title. Which the machine and deep learning people will not stand and they will protest for the data 😅 .IntroductionBeing data this important, when we have a dataset containing...

2w

Cross-Validation with Code in Python

Yes, we’ll code 5 different techniques here!Cross-Validation is one of the most efficient ways of interpreting the model performance. It ensures that the model accurately fits the data and also checks for any Overfitting. It is the process of assessing how the results of a statistical analysis will generalize to an independent dataset.Overfitting occurs...

2w

Optimization

Case Study: Optimization in Python Using GekkoProblem ScopeNow let’s dive in to find out what would be the optimal solution in which we maximize product sales by manufacturing appropriate product units under the conditions implied above!First, import ‘gekko’. If you haven’t installed it — -pip install gekko from the terminal as seen below:Next, import...

2w

Oozie — What, Why and When!

Oozie — What, Why and When!Understand the concepts of Oozie and implement in GCP dataproc cluster.Photo by Markus Spiske on UnsplashLets start with: what is oozie?Oozie is a workflow scheduler system to manage Apache Hadoop jobs. Oozie Workflow jobs are Directed Acyclic Graphs (DAGs) of actions.Workflows, Coordinators, Bundles all come together to form...

2w

GauGan: Generating Photorealistic Images from Drawings

Paper To Code implementation of NVIDIA’s GauGan on a custom Landscape ‘s Dataset. Generating photorealistic-ish:p images from drawingsGenerative Adversarial Networks (GAN) have shown to be extremely powerful in producing amazing generative models that can make music, write poetry and even generating incredibly real-looking faces.“the most interesting...

2w