,
A comprehensive beginners guide for Linear, Ridge and Lasso Regression
Introduction I was talking to one of my friends who happens to be an operations manager at one of the Supermarket chains in India. …
,
Introductory guide to Generative Adversarial Networks (GANs) and their promise!
Introduction Neural Networks have made great progress. They now recognize images and voice at levels comparable to humans. They are also able to understand natural …
,
Which algorithm takes the crown: Light GBM vs XGBOOST?
Introduction If you are an active member of the Machine Learning community, you must be aware of Boosting Machines and their capabilities. The development …
,
An Intuitive Understanding of Word Embeddings: From Count Vectors to Word2Vec
Introduction Before we start, have a look at the below examples. You open Google and search for a news article on the ongoing Champions …
,
Building Trust in Machine Learning Models (using LIME in Python)
The value is not in software, the value is in data, and this is really important for every single company, that they understand what …
,
Launching Analytics Industry Report 2017 – Trends and Salaries in India
Introduction Let me start with laying out a recent experience: I was in middle of a large audience up-skilling themselves in analytics. Average experience in room …
,
A comprehensive beginners guide to Linear Algebra for Data Scientists
Introduction One of the most common question we get on Analytics Vidhya is: How much maths do I need to learn to be a …
,
Why are GPUs necessary for training Deep Learning models?
Introduction Most of you would have heard exciting stuff happening using deep learning. You would have also heard that Deep Learning requires a lot …
,
22 must watch talks on Python for Deep Learning, Machine Learning & Data Science (from PyData 2017, Amsterdam)
Introduction Python is increasingly gaining popularity among machine learning and data science communities across the world – and for the right reasons. It probably …
,
Winners solutions & approach: The QuickSolver MiniHack, DataFest 2017
Introduction The best way to learn data science is to work on data problems and solve them. What is even better is to solve …
