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Predicting Movie Genres using NLP – An Awesome Introduction to Multi-Label Classification
Introduction I was intrigued going through this amazing article on building a multi-label image classification model last week. The data scientist in me started …
A Hands-On Introduction to Deep Q-Learning using OpenAI Gym in Python
Introduction I have always been fascinated with games. The seemingly infinite options available to perform an action under a tight timeline – it’s a …
8 Useful R Packages for Data Science You Aren’t Using (But Should!)
Introduction I’m a big fan of R – it’s no secret. I have relied on it since my days of learning statistics back in …
Build your First Multi-Label Image Classification Model in Python
Introduction Are you working with image data? There are so many things we can do using computer vision algorithms: Object detection Image segmentation Image …
DataHack Radio #21: Detecting Fake News using Machine Learning with Mike Tamir, Ph.D.
Introduction Fake news is one of the biggest scourges in our digitally connected world. That is no exaggeration. It is no longer limited to …
Top 5 Interesting Applications of GANs for Every Machine Learning Enthusiast!
Introduction Can you guess what’s common among all the faces in this image? None of these people are real! These faces were generated by …
Top 5 Machine Learning GitHub Repositories and Reddit Discussions from March 2019
Introduction GitHub repositories and Reddit discussions – both platforms have played a key role in my machine learning journey. They have helped me develop …
Computer Vision Tutorial: A Step-by-Step Introduction to Image Segmentation Techniques (Part 1)
Introduction What’s the first thing you do when you’re attempting to cross the road? We typically look left and right, take stock of the …
Nuts and Bolts of Reinforcement Learning: Introduction to Temporal Difference (TD) Learning
Introduction Q-learning became a household name in data science when DeepMind came up with an algorithm that reached superhuman levels on ATARI games. It’s …
16 OpenCV Functions to Start your Computer Vision journey (with Python code)
Introduction Computer vision is among the hottest fields in any industry right now. It is thriving thanks to the rapid advances in technology and …
Infographic: 11 Steps to Transition into Data Science (for Reporting / MIS / BI Professionals)
Introduction Do you often work with reports in Excel? Or regularly build dashboards and visualizations in Tableau or Power BI? If you answered yes …
DataHack Radio #20: Building Interpretable Machine Learning Models with Christoph Molnar
Introduction How do we build interpretable machine learning models? Or, in other words, how do we build trust in the models we design? This …
8 Excellent Pretrained Models to get you Started with Natural Language Processing (NLP)
Introduction Natural Language Processing (NLP) applications have become ubiquitous these days. I seem to stumble across websites and applications regularly that are leveraging NLP …
5 Amazing Deep Learning Frameworks Every Data Scientist Must Know! (with Illustrated Infographic)
Introduction I have been a programmer since before I can remember. I enjoy writing codes from scratch – this helps me understand that topic …
A Step-by-Step NLP Guide to Learn ELMo for Extracting Features from Text
Introduction I work on different Natural Language Processing (NLP) problems (the perks of being a data scientist!). Each NLP problem is a unique challenge in …
29 Inspiring Women Blazing a Trail in the Data Science World
This article has been updated on Women’s Day, 2019. Introduction This women’s day, we at Analytics Vidhya are celebrating the power of women in …
DataHack Radio #19: The Path to Artificial General Intelligence with Professor Melanie Mitchell
Introduction “People underestimate how complex intelligence is.” How close are we to Artificial General Intelligence (AGI)? It seems we take a step closer to …
Hands-On Introduction to creditR: An Amazing R Package to Enhance Credit Risk Scoring and Validation
Introduction Machine learning is disrupting multiple and diverse industries right now. One of the biggest industries to be impacted – finance. Functions like fraud …
11 Steps to Transition into Data Science (for Reporting / MIS / BI Professionals)
Introduction The rapid rise of data science as a professional field has lured in people from all backgrounds. Engineers, computer scientists, marketing and finance …
Top 5 Data Science GitHub Repositories and Reddit Discussions (February 2019)
Introduction I love GitHub. I have been a regular daily user of the various features the platform offers. That wasn’t always the case, however. …
