Python

Learning Phrases From Unsupervised Text (Collocation Extraction) We can easily create bi-grams with our unsupervised corpus and take it as an input to Word2Vec. For example, the sentence “I walked … Read more

Just like a watched pot never boils, a watched for loop never ends. When dealing with large datasets, even the simplest operations can take hours. Progress bars can help make … Read more

Reduce training time for deep neural networks by using many GPUs Marenostrum Supercomputer — Barcelona Supercomputing Center https://bsc.es (This post will be used in my master course SA-MIRI at UPC Barcelona Tech with … Read more

Flask API, Document Classification, Spam Filter By far, we have developed many machine learning models, generated numeric predictions on the testing data, and tested the results. And we did everything offline. … Read more

The profession of reality is moving into the 21st century, and as you can imagine home listings are flooding the internet. If you have ever looked at buying a home, … Read more

Introduction to Plotly Plotly is a company that makes visualization tools including a Python API library. (Plotly also makes Dash, a framework for building interactive web-based applications with Python code). For … Read more

Find specific elements in the page The created BeautifulSoup object can now be used to find elements in the HTML. When we inspected the website we saw that every list item … Read more

A recurring subject in NLP is to understand large corpus of texts through topic extraction. Whether you analyze users’ online reviews, product descriptions, or text entered in search bars, understanding … Read more

Alright, better to implement PCA to get the image. Let’s start by making 5 *10 matrix, and take steps of the process. Matrix X import numpy as npX = np.random.rand(5,10) … Read more

For aspiring data scientist it might sometimes be difficult to find their way through the forest of preprocessing techniques. Sklearn its preprocessing library forms a solid foundation to guide you … Read more

An Application of Sequence Model to Mine Waze Open Data of Traffic Incidents, using Python and Keras. In this tutorial, I will show you how to use RNN deep learning model … Read more

So… no pandas ?? There are some issues with pandas that the original author Wes McKinney outlines in his insightful blogpost: “Apache Arrow and the “10 Things I Hate About pandas”. … Read more

Objective Companies nowadays use music classification, either to be able to place recommendations to their customers (such as Spotify, Soundcloud) or simply as a product (for example Shazam). Determining music … Read more

Hermione interrupted them. “Aren’t you two ever going to read Hogwarts, A History?” How many times throughout the Harry Potter series does Hermione bug Harry and Ron to read the … Read more

Photo credit: Lynda.com Conditional Random Fields, Sequence Prediction, Sequence Labelling Parsing XML is a process that is designed to read XML and create a way for programs to use XML. … Read more

Introduction As a data scientist, I often find myself looking for external data sources that could be relevant for my machine learning projects. The problem is that it is uncommon … Read more

Detecting multiple objects in images and tracking them in videos In my previous story, I went over how to train an image classifier in PyTorch, with your own images, and then … Read more

In the previous part (Part I) of the word representation series, I talked about fixed word representations that make no assumption about semantics (meaning) and similarity of words. In this … Read more

Deploying a Python app in Heroku! Do you like Data Science? <Shakes head up and down> Do you like Data Science DIY deployment? <Shakes head left and right> Me neither. One … Read more

A hands on guide for beginners on EDA and Data Science competitions Exploratory Data Analysis (EDA) is an approach to analysing data sets to summarize their main characteristics, often with … Read more

Nov 5, 2018 What is PyTorch? It’s a Python-based package to serve as a replacement for Numpy arrays and to provide a flexible library forDeep Learning Development Platform. As for the … Read more

Basic concepts and mathematics There are two kinds of variables in a linear regression model: The input or predictor variable is the variable(s) that help predict the value of the … Read more

Now, back to our formula 3.49: The definition of Entropy for a probability distribution (from The Deep Learning Book) I(x) is the information content of X. I(x) itself is a random … Read more

Sep 29, 2018 Nearly all sectors use time series data to forecast future time points. Forecasting future can assist analysts and management in making better calculated decisions to maximise returns … Read more

Aug 29, 2018 Picture taken from Pixabay In this post and the next, we will look at one of the trickiest and most critical problems in Machine Learning (ML): Hyper-parameter tuning. … Read more

Aug 28, 2018 Image quality is a notion that highly depends on observers. Generally, it is linked to the conditions in which it is viewed; therefore, it is a highly subjective … Read more

Jul 8, 2018 In this tutorial we will discuss about integrating PySpark and XGBoost using a standard machine learing pipeline. We will use data from the Titanic: Machine learning from … Read more

Oct 29, 2016 Update: April 29, 2019. Updated some of the code to not use ggplot but instead use seaborn and matplotlib. I also added an example for a 3d-plot. … Read more