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    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 steps in accessing and...

    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...

    Computer Vision in Deep Learning: An Introductory Guide

    Computer vision is one of the most advanced and fascinating fields of data science, allowing computer technology to see as humans do and to represent...

    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.  ...

    What Is Reinforcement Learning and How Is It Used?

    When you do something well, you’re rewarded. This simple principle has guided humans since the beginning of time, and now, more than ever before, it...

    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...

    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...

    The Future of Data Science - Mining GTC 2021 for Trends

    Deep learning enthusiasts are increasingly putting NVIDIA’s GTC at the top of their gotta-be-there conference list. I enjoyed mining this year’s...

    Trending Toward Concept Building - A Review of Model Interpretability for Deep Neural Networks

    We are at an interesting time in our industry when it comes to validating models - a crossroads of sorts when you think about it. There is an...

    The Curse of Dimensionality

    Guest Post by Bill Shannon, Founder and Managing Partner of BioRankings Danger of Big Data Big data is the rage. This could be lots of rows (samples)...

    Evaluating Generative Adversarial Networks (GANs)

    This article provides concise insights into GANs to help data scientists and researchers assess whether to investigate GANs further. If you are...

    Data Drift Detection for Image Classifiers

    This article covers how to detect data drift for models that ingest image data as their input in order to prevent their silent degradation in...

    Natural Language Processing in Python using spaCy: An Introduction

    This article provides a brief introduction to natural language using spaCy and related libraries in Python. The complementary Domino project is also...

    Deep Reinforcement Learning

    This article provides an excerpt "Deep Reinforcement Learning" from the book, Deep Learning Illustrated by Krohn, Beyleveld, and Bassens. The article...

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