Facebook Ads Versus Facebook Boost: The Marketer’s Guide

Though it’s hard to keep up with Facebook’s constantly changing algorithm that determines how and why content shows up in users’ feeds, the social media giant remains the go-to platform for multi-location businesses to connect with customers on the local level.
And why not? Facebook’s family of services (Facebook, WhatsApp, Instagram, and Messenger) boasts a whopping 2.

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What Is BERT? – Whiteboard Friday

Posted by BritneyMullerThere’s a lot of hype and misinformation about the new Google algorithm update. What actually is BERT, how does it work, and why does it matter to our work as SEOs? Join our own machine learning and natural language processing expert Britney Muller as she breaks down exactly what BERT is and what it means for the search industry.

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Roulette Wheel Selection Using SQL

Roulette wheel selection is a very useful algorithm found in many applications such as Genetic Algorithm(GA). In GA solutions with higher fitness values are given larger probabilities of being selected to produce children, just like natural evolution. I implemented an Oracle SQL version of the Roulette wheel selection algorithm.

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Verifying and adjusting your data labels to create higher quality training datasets with Amazon SageMaker Ground Truth

Building a highly accurate training dataset for your machine learning (ML) algorithm is an iterative process. It is common to review and continuously adjust your labels until you are satisfied that the labels accurately represent the ground truth, or what is directly observable in the real world.

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Verifying and adjusting your data labels to create higher quality training datasets with Amazon SageMaker Ground Truth | Amazon Web Services

Building a highly accurate training dataset for your machine learning (ML) algorithm is an iterative process. It is common to review and continuously adjust your labels until you are satisfied that the labels accurately represent the ground truth, or what is directly observable in the real world.

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Measuring the Stability of Machine Learning Algorithms

When you think of a machine learning algorithm, the first metric that comes to mind is its accuracy. A lot of research is centered on developing algorithms that are accurate and can predict the outcome with a high degree of confidence. During the training process, an important issue to think about is the stability of the learning algorithm.

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Do AIs dream of pwning FF leagues?

In a previous post, I looked at how the established value based drafting (VBD) algorithm for picking fantasy football rosters would perform in a league of typical human players.  It turned out that we get different performance depending on if we look at ranks of VBD drafters based (i) on expected preseason player forecasts or (ii) on actual points scored by a player that season.

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Meanshift Algorithm for the Rest of Us (Python)

What is Meanshift?
Meanshift is a clustering algorithm that assigns the datapoints to the clusters iteratively by shifting points towards the mode. The mode can be understood as the highest density of datapoints (in the region, in the context of the Meanshift). As such, it is also known as the mode-seeking algorithm.

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Moving Beyond CTR: Better Recommendations Through Human Evaluation

Imagine you’re building a recommendation algorithm for your new online site. How do you measure its quality, to make sure that it’s sending users relevant and personalized content? Click-through rate may be your initial hope…but after a bit of thought, it’s not clear that it’s the best metric after all.
Take Google’s search engine.

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Initialization of deep networks

As we all know, the solution to a non-convex optimization algorithm (like
stochastic gradient descent) depends on the initial values of the parameters.
This post is about choosing initialization parameters for deep networks and how
it affects the convergence. We will also discuss the related topic of vanishing
gradients.

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