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10 Advanced Deep Learning Architectures Data Scientists Should Know!
Introduction It is becoming very hard to stay up to date with recent advancements happening in deep learning. Hardly a day goes by without …
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30 Questions to test a Data Scientist on Deep Learning (Solution – Skill test, July 2017)
Introduction Whether you are a novice at data science or a veteran, Deep learning is hard to ignore. And it deserves the attention, as …
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Debugging & Visualising training of Neural Network with TensorBoard
Introduction I started my deep learning journey a few years back. I have learnt a lot in this period. But, even after all these …
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Architecture of Convolutional Neural Networks (CNNs) demystified
Introduction I will start with a confession – there was a time when I didn’t really understand deep learning. I would look at the …
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Hands on with Deep Learning – Solution for Age Detection Practice Problem
Introduction It is one thing to learn data science by reading or watching a video / MOOC and other to apply it on problems. …
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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 …
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Getting started with Deep Learning using Keras and TensorFlow in R
Introduction It has always been a debatable topic to choose between R and Python. The Machine Learning world has been divided over the preference …
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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 …
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Transfer learning & The art of using Pre-trained Models in Deep Learning
Introduction Neural networks are a different breed of models compared to the supervised machine learning algorithms. Why do I say so? There are multiple …
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Understanding and coding Neural Networks From Scratch in Python and R
Introduction You can learn and practice a concept in two ways: Option 1: You can learn the entire theory on a particular subject and …
