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    N-shot and Zero-shot learning with Python

      Introduction In a previous post we talked about how advances in deep learning neural networks have allowed significant improvements in learning performance, resulting in...

    A Hands-on Tutorial for Transfer Learning in Python

    Fitting complex neural network models is a computationally heavy process, which requires access to large amounts of data. In this article we...

    Getting started with k-means clustering in Python

    Imagine you are an accomplished marketeer establishing a new campaign for a product and want to find appropriate segments to target, or you are...

    Getting Started with OpenCV

    In this article we talk about the foundations of Computer vision, the history and capabilities of the OpenCV framework, and how to make your first...

    Speeding up Machine Learning with parallel C/C++ code execution via Spark

    The C programming language was introduced over 50 years ago and it has consistently occupied the most used programming languages list ever since....

    Semi-uniform strategies for solving K-armed bandits

    In a previous blog post we introduced the K-armed bandit problem - a simple example of allocation of a limited set of resources over time and under...

    Increasing model velocity for complex models by leveraging hybrid pipelines, parallelization and GPU acceleration

    Data science is facing an overwhelming demand for CPU cycles as scientists try to work with datasets that are growing in complexity faster than...

    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...

    Supervised vs. Unsupervised Learning: What’s the Difference?

    Of all the thousands of algorithms available for machine learning, or ML, the vast majority use one of three main branches of learning techniques.  ...

    Powering Up Machine Learning with GPUs

    Whether you are a machine learning enthusiast, or a ninja data scientist training models for all sorts of applications, you may have heard of the...

    A Guide to Natural Language Processing for Text and Speech

    While humans have been using language since we arose, a complete understanding of language is a lifelong pursuit that often comes short, even for...

    A Detailed Guide To Transfer Learning and How It Works

    For data science teams working with inadequate data or too much data and not enough time or resources to process it, transfer learning can represent...

    The Importance of Machine Learning Model Validation and How It Works

    Model validation is a core component of developing machine learning or artificial intelligence (ML/AI). While it’s separate from training and...

    Machine Learning Model Training: What It Is and Why It’s Important

    Training a machine learning (ML) model is a process in which a machine learning algorithm is fed with training data from which it can learn. ML...

    A Guide to Machine Learning Model

    Machine learning is a subset of artificial intelligence (AI) that uses algorithms to learn from trends, data sets and certain behaviors. This process...

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