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Mathematics behind Machine Learning – The Core Concepts you Need to Know

Learn Mathematics behind machine learning. In this article explore different math aspacts- linear algebra, calculus, probability and much more.

Knowledge Graph: Data Science Technique to Mine Information from Text (with Python code)

Exlpore knowledge graphs, including their representation, entity extraction, relation extraction, and practical steps to build. Read More!

7 Amazing NLP Hack Sessions to Watch out for at DataHack Summit 2019

Exclusive Hack Sessions on Natural Language Processing (NLP) by the world-renowned experts at DataHack Summit 2019 in Bengaluru. You can't miss being there!

Hands-On Introduction to Web Scraping in Python: A Powerful Way to Extract Data for your Data Science Project

Web scraping is a useful way to collect data for data science projects. In this tutorial Learn web scraping in Python using the BeautifulSoup example.

What is SIFT(Scale Invariant Feature Transform) Algorithm?

Learn about SIFT(scale invariant feature transform), a powerful algorithm in computer vision. Understand what it is, sift computer vision.

Deployed your Machine Learning Model? Here’s What you Need to Know About Post-Production Monitoring

What happens after your machine learning model is deployed? Here's a framework to help you plan post-deployment machine learning model monitoring.

Add Shine to your Data Science Resume with these 8 Ambitious Projects on GitHub

Enhance your chances of getting hired with these 8 ambitious data science projects sourced from GitHub. These are open source data science projects.

Build an Image Classification Model using Convolutional Neural Networks in PyTorch

Learn how to build convolutional neural network (CNN) models using PyTorch. Work on an image classification problem by building CNN models.

Seaborn to Python : A Step-by-Step Guide

Level up your data visualization skills with Seaborn. Enhance your Python data science projects with visually stunning and insightful plots.

Introducing “PocketML” – an Experiential Learning Platform for Data Science