Tag: machine learning

python_tutorials
Python

Simple NLP in Python With TextBlob: Tokenization

Introduction The amount of textual data on the Internet has significantly increased in the past decades. There’s no doubt that the processing of this amount of information must be automated, and the TextBlob package is one of the fairly simple ways to perform NLP – Natural Language Processing. It provides a simple API for diving into common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, tokenization, sentiment analysis, classification, translation, and more. No special technical prerequisites […]

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Deep Learning, Intermediate, Listicle, NLP, Python, Technique Leave a comment

The Essential NLP Guide for data scientists (with codes for top 10 common NLP tasks)

Introduction Organizations today deal with huge amount and wide variety of data – calls from customers, their emails, tweets, data from mobile applications and what not. It takes a lot of effort and time to make this data useful. One of the core skills in extracting information from text data is Natural Language Processing (NLP). Natural Language Processing (NLP) is the art and science which helps us extract information from text and use it in our computations and algorithms. Given […]

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Analytics Vidhya, Beginner, Deep Learning, Listicle, Machine Learning, NLP, Winners Approach Leave a comment

The Winning Approaches from codeFest 2018 – NLP, Computer Vision and Machine Learning!

Introduction Analytics Vidhya’s hackathons are one of the best ways to evaluate how far you’ve traveled in your data science journey. And what better way than to put your skills to the test against the top data scientists from around the globe? Participating in these hackathons also helps you understand where you need to improve and what else you can learn to get a better score in the next competition. And a very popular demand after each hackathon is to […]

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Classification, Computer Vision, Deep Learning, Image, Libraries, NLP, Programming, Python, PyTorch, Supervised, Unstructured Data Leave a comment

Get Started with PyTorch – Learn How to Build Quick & Accurate Neural Networks (with 4 Case Studies!)

Introduction PyTorch v TensorFlow – how many times have you seen this polarizing question pop up on social media? The rise of deep learning in recent times has been fuelled by the popularity of these frameworks. There are staunch supporters of both, but a clear winner has started to emerge in the last year. PyTorch was one of the most popular frameworks in 2018. It quickly became the preferred go-to deep learning framework among researchers in both academia and the […]

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Classification, Machine Learning, NLP, Project, Python, Supervised, Technique, Telecom, Text, Unstructured Data Leave a comment

Predicting Movie Genres using NLP – An Awesome Introduction to Multi-Label Classification

Introduction I was intrigued going through this amazing article on building a multi-label image classification model last week. The data scientist in me started exploring possibilities of transforming this idea into a Natural Language Processing (NLP) problem. That article showcases computer vision techniques to predict a movie’s genre. So I had to find a way to convert that problem statement into text-based data. Now, most NLP tutorials look at solving single-label classification challenges (when there’s only one label per observation). […]

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python_tutorials
Python

Kernel Density Estimation in Python Using Scikit-Learn

Introduction This article is an introduction to kernel density estimation using Python’s machine learning library scikit-learn. Kernel density estimation (KDE) is a non-parametric method for estimating the probability density function of a given random variable. It is also referred to by its traditional name, the Parzen-Rosenblatt Window method, after its discoverers. Given a sample of independent, identically distributed (i.i.d) observations ((x_1,x_2,ldots,x_n)) of a random variable from an unknown source distribution, the kernel density estimate, is given by: $$p(x) = frac{1}{nh} […]

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Python

Facial Detection in Python with OpenCV

Introduction Facial detection is a powerful and common use-case of Machine Learning. It can be used to automatize manual tasks such as school attendance and law enforcement. In the other hand, it can be used for biometric authorization. In this article, we’ll perform facial detection in Python, using OpenCV. OpenCV OpenCV is one of the most popular computer vision libraries. It was written in C and C++ and also provides support for Python, besides Java and MATLAB. While it’s not […]

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python_tutorials
Python

Deep Learning in Keras – Building a Deep Learning Model

Introduction Deep learning is one of the most interesting and promising areas of artificial intelligence (AI) and machine learning currently. With great advances in technology and algorithms in recent years, deep learning has opened the door to a new era of AI applications. In many of these applications, deep learning algorithms performed equal to human experts and sometimes surpassed them. Python has become the go-to language for Machine Learning and many of the most popular and powerful deep learning libraries […]

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python_tutorials
Python

Translating Strings in Python with TextBlob

Introduction Text translation is a difficult computer problem that gets better and easier to solve every year. Big companies like Google are actively working on improving their text translation services which enables the rest of us to use them freely. Apart from their great personal use, these services can be used by developers through various APIs. This article is about TextBlob which uses one such API to perform text translation. What is TextBlob? TextBlob is a text-processing library written in […]

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Analytics Vidhya, Beginner, Career, Profile Building, Winners Approach Leave a comment

How I Became a Data Science Competition Master from Scratch

Overview Winning data science competitions can be a complex process – but you can crack the top 3 if you have a framework to follow Hear from a top data science hackathon expert and how he went from scratch to winning data science competitions   Introduction There is no alternative to learning through experience. Especially in the data science industry! I recently won the top prize in Zindi’s Zimnat Insurance Recommendation challenge – an achievement that ranks top among my […]

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