Articles About Deep Learning

The Top GitHub Repositories & Reddit Threads Every Data Scientist should know (June 2018)

Introduction Half the year has flown by and that brings us to the June edition of our popular series – the top GitHub repositories and Reddit threads from last month. During the course of writing these articles, I have learned so much about machine learning from either open source codes or invaluable discussions among the top data science brains in the world. What makes GitHub special is not just it’s code hosting and social collaboration features for data scientists. It […]

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The 25 Best Data Science and Machine Learning GitHub Repositories from 2018

Introduction What’s the best platform for hosting your code, collaborating with team members, and also acts as an online resume to showcase your coding skills? Ask any data scientist, and they’ll point you towards GitHub. It has been a truly revolutionary platform in recent years and has changed the landscape of how we host and even do coding. But that’s not all. It acts as a learning tool as well. How, you ask? I’ll give you a hint – open […]

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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 (or technique) clearly. This approach is especially helpful when we’re learning data science initially. Try to implement a neural network from scratch and you’ll understand a lot of interest things. But do you think this is a good idea when building deep learning models on a real-world dataset? It’s definitely possible if you have days or […]

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2019 In-Review and Trends for 2020 – A Technical Overview of Machine Learning and Deep Learning!

Overview A comprehensive look at the top machine learning highlights from 2019, including an exhaustive dive into NLP frameworks Check out the machine learning trends in 2020 – and hear from top experts like Sudalai Rajkumar and Dat Tran!   Introduction 2020 is almost upon us! It’s time to welcome the new year with a splash of machine learning sprinkled into our brand new resolutions. Machine learning will continue to be at the heart of what we do and how […]

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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 trophy and get hundreds of search results in return about it. Nate silver analysed millions of tweets and correctly predicted the results of 49 out of 50 states in 2008 U.S Presidential Elections. You type a sentence in google translate in English and get an Equivalent Chinese conversion.   So what do the above examples have […]

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The Ultimate Learning Path to Becoming a Data Scientist in 2018

Introduction So you’ve taken the plunge. You want to become a data scientist. But where to begin? There are far too many resources out there. How do you decide the starting point? Did you miss out on topics you should have studied? Which are the best resources to learn? Don’t worry, we have you covered! Analytics Vidhya’s learning path for 2016 saw 250,000+ views. In 2017, we went even further and saw an incredible 500,000+ views! So this year, we […]

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An Introductory Guide to Understand how ANNs Conceptualize New Ideas (using Embedding)

Introduction Here’s something you don’t hear everyday – everything we perceive is just a best case probabilistic prediction by our brain, based on our past encounters and knowledge gained through other mediums. This might sound extremely counter intuitive because we have always imagined that our brain mostly gives us deterministic answers. We’ll do a small experiment to showcase this logic. Take a look at the below image: Q1. Do you see a human ? Q2. Can you identify the person? […]

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Tutorial on Text Classification (NLP) using ULMFiT and fastai Library in Python

Introduction Natural Language Processing (NLP) needs no introduction in today’s world. It’s one of the most important fields of study and research, and has seen a phenomenal rise in interest in the last decade. The basics of NLP are widely known and easy to grasp. But things start to get tricky when the text data becomes huge and unstructured. That’s where deep learning becomes so pivotal. Yes, I’m talking about deep learning for NLP tasks – a still relatively less […]

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An Exhaustive Guide to Detecting and Fighting Neural Fake News using NLP

Overview Neural fake news (fake news generated by AI) can be a huge issue for our society This article discusses different Natural Language Processing methods to develop robust defense against Neural Fake News, including using the GPT-2 detector model and Grover (AllenNLP) Every data science professional should be aware of what neural fake news is and how to combat it   Introduction Fake news is a major concern in our society right now. It has gone hand-in-hand with the rise […]

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A Comprehensive Step-by-Step Guide to Become an Industry-Ready Data Science Professional

Introduction to Artificial Intelligence and Machine Learning Artificial Intelligence (AI) and its sub-field Machine Learning (ML) have taken the world by storm. From face recognition cameras, smart personal assistants to self-driven cars. We are moving towards a world enhanced by these recent upcoming technologies. It’s the most exciting time to be in this career field! The global Artificial Intelligence market is expected to grow to $400 billion by the year 2025. From Startups to big organizations, all want to join […]

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