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Dynamic Programming For Beginners

Explore the concept of Dynamic Programming and learn how it efficiently simplifies complex problems into manageable subproblems. Read Now!

Deep Learning Tutorial to Calculate the Screen Time of Actors in any Video (with Python codes)

A complete deep learning tutorial for video analysis using python. This article will help you understand how to use deep learning on video data.

DataHack Radio Episode #9: Data Science at Airbnb & Lyft with Dr. Alok Gupta

How do companies like Airbnb and Lyft use data science? Find out in this fascinating podcast with Lyft's Head of Data Science, Dr. Alok Gupta.

A Simple Introduction to Facial Recognition (with Python codes)

An introduction to face recognition in python. In this article learn about applications of face recognition and its implementation in python with codes.

DataHack Radio Episode #8: How Self-Driving Cars Work with Drive.ai’s Brody Huval

In this podcast, Drive.ai's co-founder Brody Huval sheds light on the various intriguing facets of self-driving cars and how to build one from scratch!

DataHack Radio Episode #7: Tackling Data Science Challenges in India with NITI Aayog’s Dr. Avik Sarkar (Independence Day Special!)

The Best Machine Learning GitHub Repositories & Reddit Threads from July 2018

Take a look at the top machine learning and data science GitHub repositories and Reddit discussions that were designed and created in July, 2018.

Comprehensive Hands on Guide to Twitter Sentiment Analysis with dataset and code

The task is to detect hate speech in tweets using Sentiment Analysis. In this tut, we will follow a sequence of steps needed to solve a sentiment analysis

Top 10 Pretrained Models to get you Started with Deep Learning (Part 1 – Computer Vision)

Top 10 pre trained deep learning models for the field of computer vision. In this article learn how you can get started with them.

DataHack Radio Episode #5: Building High Performance Data Science teams with Kiran R

This a MUST-LISTEN podcast that covers a variety of topics ranging from machine learning competitions to how a data science team is typically structured.