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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Gradient Descent in Python: Implementation and Theory

Introduction This tutorial is an introduction to a simple optimization technique called gradient descent, which has seen major application in state-of-the-art machine learning models. We’ll develop a general purpose routine to implement gradient descent and apply it to solve different problems, including classification via supervised learning. In this process, we’ll gain an insight into the working of this algorithm and study the effect of various hyper-parameters on its performance. We’ll also go over batch and stochastic gradient descent variants as […]

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Framework to build a niche dictionary for text mining

Having the right dictionary is at the heart of any text mining analysis. Dictionary for text mining can be compared to maps while travelling in a new city. The more precise and accurate maps you use, the faster you reach to the destination. On the other hand, a wrong or incomplete map can end up confusing the traveler. Use of dictionary helps us convert unstructured text into structured data. The more precise dictionary you have for the analysis, the more accurate […]

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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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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 its own way. That’s just a reflection of how complex, beautiful and wonderful the human language is. But one thing has always been a thorn in an NLP practitioner’s mind is the inability (of machines) to understand the true meaning of a sentence. Yes, I’m talking about context. Traditional NLP techniques and frameworks were great when […]

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Top 5 Data Science GitHub Repositories and Reddit Discussions (January 2019)

Introduction There’s nothing quite like GitHub and Reddit for data science. Both platforms have been of immense help to me in my data science journey. GitHub is the ultimate one-stop platform for hosting your code. It excels at easing the collaboration process between team members. Most leading data scientists and organizations use GitHub to open-source their libraries and frameworks. So not only do we stay up-to-date with the latest developments in our field, we get to replicate their models on our […]

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Comprehensive Guide to Text Summarization using Deep Learning in Python

Introduction “I don’t want a full report, just give me a summary of the results”. I have often found myself in this situation – both in college as well as my professional life. We prepare a comprehensive report and the teacher/supervisor only has time to read the summary. Sounds familiar? Well, I decided to do something about it. Manually converting the report to a summarized version is too time taking, right? Could I lean on Natural Language Processing (NLP) techniques […]

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A Comprehensive Guide to Build your own Language Model in Python!

Overview Language models are a crucial component in the Natural Language Processing (NLP) journey These language models power all the popular NLP applications we are familiar with – Google Assistant, Siri, Amazon’s Alexa, etc. We will go from basic language models to advanced ones in Python here   Introduction We tend to look through language and not realize how much power language has. Language is such a powerful medium of communication. We have the ability to build projects from scratch […]

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Python: How to Flatten a List of Lists

Introduction A list is the most flexible data structure in Python. Whereas, a 2D list which is commonly known as a list of lists, is a list object where every item is a list itself – for example: [[1,2,3], [4,5,6], [7,8,9]]. Flattening a list of lists entails converting a 2D list into a 1D list by un-nesting each list item stored in the list of lists – i.e., converting [[1, 2, 3], [4, 5, 6], [7, 8, 9]] into [1, […]

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Python: Slice Notation on Tuple

Introduction The term slicing in programming usually refers to obtaining a substring, sub-tuple, or sublist from a string, tuple, or list respectively. Python offers an array of straightforward ways to slice not only these three but any iterable. An iterable is, as the name suggests, any object that can be iterated over. In this article, we’ll go over everything you need to know about Slicing Tuples in Python. Slicing a Tuple in Python There are a couple of ways to […]

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