Category: Computer Vision
A Review of 2020 and Trends in 2021 – A Technical Overview of Machine Learning and Deep Learning!
Introduction Data science is not a choice anymore. It is a necessity. 2020 is almost in the books now. What a crazy year from whichever standpoint you look at it. A pandemic raged around the world and yet it failed to dim the light on data science. The thirst to learn more continued unabated in our community and we saw some incredible developments and breakthroughs this year. From OpenAI’s mind-boggling GPT-3 framework to Facebook’s DETR model, this was a year […]
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Top 15 Open-Source Datasets of 2020 that every Data Scientist Should add to their Portfolio!
Overview Here is a list of Top 15 Datasets for 2020 that we feel every data scientist should practice on The article contains 5 datasets each for machine learning, computer vision, and NLP By no means is this list exhaustive. Feel free to add other datasets in the comments below Introduction For the things we have to learn before we can do them, we learn by doing them -Aristotle I am sure everyone can attest to this saying. No […]
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Top 5 Machine Learning GitHub Repositories & Reddit Discussions (October 2018)
Introduction “Should I use GitHub for my projects?” – I’m often asked this question by aspiring data scientists. There’s only one answer to this – “Absolutely!”. GitHub is an invaluable platform for data scientists looking to stand out from the crowd. It’s an online resume for displaying your code to recruiters and other fellow professionals. The fact that GitHub hosts open-source projects from the top tech behemoths like Google, Facebook, IBM, NVIDIA, etc. is what adds to the gloss of […]
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A Hands-on Tutorial to Learn Attention Mechanism For Image Caption Generation in Python
Overview Understand the attention mechanism for image caption generation Implement attention mechanism to generate caption in python Introduction The attention mechanism is a complex cognitive ability that human beings possess. When people receive information, they can consciously ignore some of the main information while ignoring other secondary information. This ability of self-selection is called attention. The attention mechanism allows the neural network to have the ability to focus on its subset of inputs to select specific features. In recent […]
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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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Handling Imbalanced Data – Machine Learning, Computer Vision and NLP
This article was published as a part of the Data Science Blogathon. Introduction: In the real world, the data we gather will be heavily imbalanced most of the time. so, what is an Imbalanced Dataset?. The training samples are not equally distributed across the target classes. For instance, if we take the case of the personal loan classification problem, it is effortless to get the ‘not approved’ data, in contrast to, ‘approved’ details. As a result, the model is more […]
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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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