About George Seif

George Seif is a Machine Learning Engineer and passionate technologist. He's driven to bringing the most cutting edge technologies to life by building real-world, applicable products. He classifies himself as a Certified Nerd.

George Seif Posts (19)

  • An Easy Introduction to Machine Learning Recommender Systems - 04 Sep 2019
    Recommender systems are an important class of machine learning algorithms that offer "relevant" suggestions to users. Categorized as either collaborative filtering or a content-based system, check out how these approaches work along with implementations to follow from example code.
  • Silver BlogThe Easy Way to Do Advanced Data Visualisation for Data Scientists - 13 Aug 2019
    Creating effective data visualisations is a core skill for data scientists. This tutorial will guide you through how to easily develop interactive visualisations using the Python library plotly.
  • Here’s how you can accelerate your Data Science on GPU - 30 Jul 2019
    Data Scientists need computing power. Whether you’re processing a big dataset with Pandas or running some computation on a massive matrix with Numpy, you’ll need a powerful machine to get the job done in a reasonable amount of time.
  • Easy, One-Click Jupyter Notebooks - 24 Jul 2019
    All of the setup for software, networking, security, and libraries is automatically taken care of by the Saturn Cloud system. Data Scientists can then focus on the actual Data Science and not the tedious infrastructure work that falls around it
  • Nvidia’s New Data Science Workstation — a Review and Benchmark - 03 Jul 2019
    Nvidia has recently released their Data Science Workstation, a PC that puts together all the Data Science hardware and software into one nice package. The workstation is a total powerhouse machine, packed with all the computing power — and software — that’s great for plowing through data.
  • One Simple Trick for Speeding up your Python Code with Numpy - 19 Jun 2019
    Looping over Python arrays, lists, or dictionaries, can be slow. Thus, vectorized operations in Numpy are mapped to highly optimized C code, making them much faster than their standard Python counterparts.
  • Gold Blog 5 Useful Statistics Data Scientists Need to Know - 14 Jun 2019
    A data scientist should know how to effectively use statistics to gain insights from data. Here are five useful and practical statistical concepts that every data scientist must know.
  • How to do Everything in Computer Vision - 27 Feb 2019
    The many standard tasks in computer vision all require special consideration: classification, detection, segmentation, pose estimation, enhancement and restoration, and action recognition. Let me show you how to do everything in Computer Vision with Deep Learning!
  • Gold BlogHow to Setup a Python Environment for Machine Learning - 18 Feb 2019
    In this tutorial, you will learn how to set up a stable Python Machine Learning development environment. You’ll be able to get right down into the ML and never have to worry about installing packages ever again.
  • Gold BlogAn Introduction to Scikit Learn: The Gold Standard of Python Machine Learning - 13 Feb 2019
    If you’re going to do Machine Learning in Python, Scikit Learn is the gold standard. Scikit-learn provides a wide selection of supervised and unsupervised learning algorithms. Best of all, it’s by far the easiest and cleanest ML library.

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