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How to do Everything in Computer Vision
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!
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 How to Setup a Python Environment for Machine Learning
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.
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An Introduction to Scikit Learn: The Gold Standard of Python Machine Learning
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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The 6 Most Useful Machine Learning Projects of 2018
By George Seif, AI / Machine Learning Engineer on January 15, 2019 in Automated Machine Learning, Facebook, fast.ai, Google, Keras, Machine Learning, Object Detection, Python, Reinforcement Learning, Word EmbeddingsLet’s take a look at the top 6 most practically useful ML projects over the past year. These projects have published code and datasets that allow individual developers and smaller teams to learn and immediately create value.
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Handling Imbalanced Datasets in Deep Learning
It’s important to understand why we should do it so that we can be sure it’s a valuable investment. Class balancing techniques are only really necessary when we actually care about the minority classes.
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The 5 Basic Statistics Concepts Data Scientists Need to Know
Today, we’re going to look at 5 basic statistics concepts that data scientists need to know and how they can be applied most effectively!
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Get a 2–6x Speed-up on Your Data Pre-processing with Python
Get a 2–6x speed-up on your pre-processing with these 3 lines of code!
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5 “Clean Code” Tips That Will Dramatically Improve Your Productivity
TL;DR: If it isn’t tested, it’s broken; Choose meaningful names; Classes and functions should be small and obey the Single Responsibility Principle (SRP); Catch and handle exceptions, even if you don’t think you need to; Logs, logs, logs
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Selecting the Best Machine Learning Algorithm for Your Regression Problem
This post should then serve as a great aid in selecting the best ML algorithm for you regression problem!
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5 Quick and Easy Data Visualizations in Python with Code
This post provides an overview of a small number of widely used data visualizations, and includes code in the form of functions to implement each in Python using Matplotlib.
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How to Setup a Python Environment for Machine Learning
The 5 Basic Statistics Concepts Data Scientists Need to Know
5 Quick and Easy Data Visualizations in Python with Code