Skip to content
    Latest

    Tensorflow, PyTorch or Keras for Deep Learning

    Machine learning provides us with ways to create data-powered systems that learn and enhance themselves, without being specifically programmed for the task at hand. As...

    Reinforcement Learning: The K-armed bandit problem

    In a previous blog post we talked about the foundations of reinforcement learning. We covered classical and operant conditioning, rewards, states,...

    KNN with Examples in Python

    In this article, we will introduce and implement k-nearest neighbours (KNN) as one of the supervised machine learning algorithms. KNN is utilised to...

    Getting Started with Ray

    In this blog post we give a quick introduction to Ray. We talk about the architecture and execution model, and present some of Ray's core paradigms...

    Getting Data with Beautiful Soup

    Data is all around us, from the spreadsheets we analyse on a daily basis, to the weather forecast we rely on every morning or the webpages we read....

    Data Exploration with Pandas Profiler and D-Tale

    We all have heard how data is the new oil. I always say that if that is the case, we need to go through some refinement process before that raw oil...

    Explaining black-box models using attribute importance, PDPs, and LIME

    In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights...

    Building a Speaker Recognition Model

    The ability of a system to recognize a person by their voice is a non-intrusive way to collect their biometric information. Unlike fingerprint...

    Building a Named Entity Recognition model using a BiLSTM-CRF network

    In this blog post we present the Named Entity Recognition problem and show how a BiLSTM-CRF model can be fitted using a freely available annotated...

    Fitting Support Vector Machines via Quadratic Programming

    In this blog post we take a deep dive into the internals of Support Vector Machines. We derive a Linear SVM classifier, explain its advantages, and...

    Credit Card Fraud Detection using XGBoost, SMOTE, and threshold moving

    In this article, we'll discuss the challenge organizations face around fraud detection, how machine learning can be used to identify and spot...

    Enterprise-class NLP with spaCy v3

    spaCy is a python library that provides capabilities to conduct advanced natural language processing analysis and build models that can underpin...

    How to Supercharge Data Exploration with Pandas Profiling

    Producing insights from raw data is a time-consuming process. Predictive modeling efforts rely on dataset profiles, whether consisting of summary...

    Density-Based Clustering

    Original content by Manojit Nandi - Updated by Josh Poduska. Cluster Analysis is an important problem in data analysis. Data scientists use...

    Subscribe to the Data Science Blog

    Receive data science tips and tutorials from leading Data Scientists right to your inbox.